Mutant-Allele Tumor Heterogeneity, a Favorable Biomarker to Assess Intra-Tumor Heterogeneity, in Advanced Lung Adenocarcinoma

The Potential Value of RPS27A in Prognosis and Immunotherapy: From Pan-Cancer Analysis to Hepatocellular Carcinoma Validation

Purpose

Elucidation of the potential value of ribosomal protein S27a (RPS27A) for prognosis and immunotherapy in pan-cancer analysis, and exploration of the oncogenic function of RPS27A on hepatocellular carcinoma (HCC) and macrophage polarization.

Methods

A systematic analysis of the function and mechanism of RPS27A was conducted with R software and multiple public platforms, including UALCAN, HPA, TISIDB, TIMER, cBioPortal, cancerSEA, TIDE, and TIMSO databases. The RPS27A expression in human and mouse liver was detected by immunohistochemistry. The biological behavior of HCC cells was detected in vitro after RPS27A overexpression. The influence of RPS27A on macrophage polarization was detected by the coculturing assay.

Results

RPS27A dysregulation was found in multiple cancer types, and RPS27A level was associated with clinicopathologic features and prognosis in human cancers. RPS27A affected cancer statuses and multiple signaling pathways, such as DNA repair, invasion, IL10 synthesis, and MAPK activation. RPS27A took part in regulations of genomic alterations and heterogeneity and was associated with tumor mutation burden, microsatellite instability, neoantigen and so on. RPS27A expression was connected to the immune subtypes, tumor purity and immune cell infiltration and participated in regulation of the immunotherapy response. RPS27A was upregulated in HCC tissues compared to normal liver tissues. RPS27A overexpression in HCC cells promoted the proliferation, migration, and invasion of cancer cells, and accelerated M2 polarization of macrophage.

Conclusion

RPS27A had the potential to be a biomarker for diagnosis, prognosis and immunotherapy response in pan-cancer, and targeting RPS27A may provide new ideas for cancer immunotherapy.

Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma

Background

Aberrant fatty acid metabolism (FAM) plays a critical role in the tumorigenesis of human malignancies. However, studies on its impact in lung adenocarcinoma (LUAD) are limited.

Methods

We developed a prognostic signature comprising 10 FAM-related genes (GPR115, SOAT2, CDH17, MOGAT2, COL11A1, TCN1, LGR5, SLC34A2, RHOV, and DKK1) using data from LUAD patients in The Cancer Genome Atlas (TCGA). This signature was validated using six independent LUAD datasets from the Gene Expression Omnibus (GEO). Patients were classified into high- and low-risk groups, and overall survival (OS) was compared by Kaplan-Meier analysis. The signature's independence as a prognostic indicator was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis validated the signature. Tumor immune microenvironment (TIME) was analyzed using ESTIMATE and multiple deconvolution algorithms. Functional assays, including CCK8, cell cycle, apoptosis, transwell, and wound healing assays, were performed on MOGAT2-silenced H1299 cells using CRISPR/Cas9 technology.

Results

Low-risk group patients exhibited decreased OS. The signature was an independent prognostic indicator and demonstrated strong risk-stratification utility for disease relapse/progression. ROC analysis confirmed the signature's validity across validation sets. TIME analysis revealed higher infiltration of CD8+ T cells, natural killers, and B cells, and lower tumor purity, stemness index, and tumor mutation burden (TMB) in low-risk patients. These patients also showed elevated T cell receptor richness and diversity, along with reduced immune cell senescence. High-risk patients exhibited enrichment in pathways related to resistance to immune checkpoint blockades, such as DNA repair, hypoxia, epithelial-mesenchymal transition, and the G2M checkpoint. LUAD patients receiving anti-PD-1 treatment had lower risk scores among responders compared to non-responders. MOGAT2 was expressed at higher levels in low-risk LUAD patients. Functional assays revealed that MOGAT2 knockdown in H1299 cells promoted proliferation and migration, induced G2 cell cycle arrest, and decreased apoptosis.

Conclusions

This FAM-related gene signature provides a valuable tool for prognostic stratification and monitoring of TIME and immunotherapy responses in LUAD. MOGAT2 is identified as a potential anti-tumor regulator, offering new insights into its role in LUAD pathogenesis.

Impact of preanalytical factors on liquid biopsy in the canine cancer model

While liquid biopsy has potential to transform cancer diagnostics through minimally-invasive detection and monitoring of tumors, the impact of preanalytical factors such as the timing and anatomical location of blood draw is not well understood. To address this gap, we leveraged pet dogs with spontaneous cancer as a model system, as their compressed disease timeline facilitates rapid diagnostic benchmarking. Key liquid biopsy metrics from dogs were consistent with existing reports from human patients. The tumor content of samples was higher from venipuncture sites closer to the tumor and from a central vein. Metrics also differed between lymphoma and non-hematopoietic cancers, urging cancer-type-specific interpretation. Liquid biopsy was highly sensitive to disease status, with changes identified soon after post chemotherapy administration, and trends of increased tumor fraction and other metrics observed prior to clinical relapse in dogs with lymphoma or osteosarcoma. These data support the utility of pet dogs with cancer as a relevant system for advancing liquid biopsy platforms.

Genomic characterization reveals distinct mutational landscapes and therapeutic implications between different molecular subtypes of triple-negative breast cancer

Triple-negative breast cancer (TNBC) has high heterogeneity, poor prognosis, and limited treatment success. Recently, an immunohistochemistry-based surrogate classification for the "Fudan University Shanghai Cancer Center (FUSCC) subtyping" has been developed and is considered more suitable for clinical application. Seventy-one paraffin-embedded sections of surgically resected TNBC were classified into four molecular subtypes using the IHC-based surrogate classification. Genomic analysis was performed by targeted next-generation sequencing and the specificity of the subtypes was explored by bioinformatics, including survival analysis, multivariate Cox regression, pathway enrichment, Pyclone analysis, mutational signature analysis and PHIAL analysis. AKT1 and BRCA1 mutations were identified as independent prognostic factors in TNBC. TNBC molecular subtypes encompass distinct genomic landscapes that show specific heterogeneities. The luminal androgen receptor (LAR) subtype was associated with mutations in PIK3CA and PI3K pathways, which are potentially sensitive to PI3K pathway inhibitors. The basal-like immune-suppressed (BLIS) subtype was characterized by high genomic instability and the specific possession of signature 19 while patients in the immunomodulatory (IM) subtype belonged to the PD-L1 ≥ 1% subgroup with enrichment in Notch signaling, suggesting a possible benefit of immune checkpoint inhibitors and Notch inhibitors. Moreover, mesenchymal-like (MES) tumors displayed enrichment in the receptor tyrosine kinase (RTK)-RAS pathway and potential sensitivity to RTK pathway inhibitors. The findings suggest potential treatment targets and prognostic factors, indicating the possibility of TNBC stratified therapy in the future.

CCDC58 is a potential biomarker for diagnosis, prognosis, immunity, and genomic heterogeneity in pan-cancer

Coiled-coil domain-containing 58 (CCDC58) is a member of the CCDC protein family. Similar to other members, CCDC58 exhibits potential tumorigenic roles in a variety of malignancies. However, there is no systematic and comprehensive pan-cancer analysis to investigate the diagnosis, prognosis, immune infiltration, and other related functions of CCDC58. We used several online websites and databases, such as TCGA, GTEx, UALCAN, HPA, CancerSEA, BioGRID, GEPIA 2.0, TIMER 2.0, and TISIDB, to extract CCDC58 expression data and clinical data of patients in pan-cancer. Then, the relationship between CCDC58 expression and diagnosis, prognosis, genetic alterations, DNA methylation, genomic heterogeneity, and immune infiltration level were determined. In addition, the biological function of CCDC58 in liver hepatocellular carcinoma (LIHC) was investigated. Pan-cancer analysis results showed that CCDC58 was differentially expressed in most tumors and showed excellent performance in diagnosis and prediction of prognosis. The expression of CCDC58 was highly correlated with genetic alterations, DNA methylation, and genomic heterogeneity in some tumors. In addition, the correlation analysis of CCDC58 with the level of immune infiltration and immune checkpoint marker genes indicated that CCDC58 might affect the composition of the tumor immune microenvironment. Enrichment analysis showed that CCDC58-related genes were mainly linked to mitosis, chromosome, and cell cycle. Finally, biological function experiments demonstrated that CCDC58 plays an important role in tumor cell proliferation and migration. CCDC58 was first identified as a pan-cancer biomarker. It may be used as a potential therapeutic target to improve the prognosis of patients in the future.

Mutant-allele dispersion correlates with prognosis risk in patients with advanced non-small cell lung cancer

BACKGROUND

Intra-tumor heterogeneity (ITH) contributes to lung cancer progression and resistance to therapy. To evaluate ITH and determine whether it may be employed as a predictive biomarker of prognosis in patients with advanced non-small cell lung cancer (NSCLC), we used a novel algorithm called mutant-allele dispersion (MAD).

METHODS

In the study, 103 patients with advanced NSCLC were enrolled. Using a panel of 425 cancer-related genes, next-generation sequencing (NGS) was performed on tumor specimens that had been collected. From NGS data, we derived MAD values, and we next looked into their relationships with clinical variables and different mutation subtypes.

RESULTS

The median MAD among 103 NSCLC patients was 0.73. EGFR mutation, tyrosine kinase inhibitor (TKI) therapy, radiotherapy, and chemotherapy cycles were all substantially correlated with the MAD score. In patients with lung adenocarcinoma (LUAD), correlation analysis revealed that the MAD score was substantially linked with Notch pathway mutation (P = 0.021). A significant relationship between high MAD and shorter progression-free survival (PFS) was found (HR = 2.004, 95%CI 1.269-3.163, P = 0.003). In patients with advanced NSCLC, histological type (P = 0.004), SMARCA4 mutation (P = 0.038), and LRP1B mutation (P = 0.006) were all independently associated with prognosis. The disease control rate was considerably greater in the low MAD group compared to the high MAD group in 19 LUAD patients receiving immunotherapy (92.9% vs. 40%, P = 0.037). TKI-PFS was longer in 37 patients with low MAD who received first-line TKI therapy (P = 0.014).

CONCLUSION

Our findings suggested that MAD is a practical and simple algorithm for assessing ITH, and populations with high MAD values are more likely to have EGFR mutations. MAD can be used as a potential biomarker to predict not only the prognosis of NSCLC but also the efficacy of immunotherapy and TKI therapy in patients with advanced NSCLC.

Genomic and Glycolytic Entropy Are Reliable Radiogenomic Heterogeneity Biomarkers for Non-Small Cell Lung Cancer

Radiogenomic heterogeneity features in ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) have become popular in non-small cell lung cancer (NSCLC) research. However, the reliabilities of genomic heterogeneity features and of PET-based glycolytic features in different image matrix sizes have yet to be thoroughly tested. We conducted a prospective study with 46 NSCLC patients to assess the intra-class correlation coefficient (ICC) of different genomic heterogeneity features. We also tested the ICC of PET-based heterogeneity features from different image matrix sizes. The association of radiogenomic features with clinical data was also examined. The entropy-based genomic heterogeneity feature (ICC = 0.736) is more reliable than the median-based feature (ICC = -0.416). The PET-based glycolytic entropy was insensitive to image matrix size change (ICC = 0.958) and remained reliable in tumors with a metabolic volume of <10 mL (ICC = 0.894). The glycolytic entropy is also significantly associated with advanced cancer stages (p = 0.011). We conclude that the entropy-based radiogenomic features are reliable and may serve as ideal biomarkers for research and further clinical use for NSCLC.