A seven-gene signature to predict the prognosis of oral squamous cell carcinoma

FTO, PIK3CB serve as potential markers to complement CEA and CA15-3 for the diagnosis of breast cancer

The diagnostic efficacy of carcinoembryonic antigen (CEA) and carbohydrate antigen 15-3 (CA15-3) is limited in breast cancer (BC), highlighting the necessity of exploring novel biomarkers to improve for BC diagnosis. Therefore, we assessed the diagnostic value of fat mass and obesity-associated protein (FTO), phosphatidylinositol-4,5-biphosphate 3-kinase catalytic subunit β (PIK3CB) as a potential complementary biomarker to CEA and CA153 in breast cancer by measuring serum FTO,PIK3CB levels. FTO, PIK3CB, CEA and CA15-3 levels were measured in 112 BC patients and 64 healthy controls using enzyme-linked immunosorbent assay or electrochemiluminescence immunoassay. Spearman's rank correlation analysis was conducted to assess the correlation between the levels of the 2 markers. The relationships between FTO, PIK3CB, CEA, CA15-3 and clinical characteristics were evaluated. Receiver operating characteristic curve (ROC) analysis was performed to assess the diagnostic value of FTO, PIK3CB, CEA and CA15-3 of BC. Serum FTO, PIK3CB, CEA and CA15-3 levels were significantly increased in BC. There was no correlation between FTO, PIK3CB and CEA, CA15-3. FTO and PIK3CB demonstrated significant diagnostic performance for breast cancer, with FTO achieving a specificity of 90.63%. The diagnostic performance of 2-four biomarker combinations was significantly superior to individual CEA or CA153, with a combined panel of 4 biomarkers yielding an area under the curve (AUC) of 0.918, sensitivity of 81.25% and specificity of 85.94%. In early-stage breast cancer (I + II), the combination of FTO, PIK3CB, CEA and CA153 yielded an AUC of 0.895, sensitivity of 77.22% and specificity of 85.71%. FTO and PIK3CB can be served as potential biomarkers to complement CEA and CA15-3 for BC diagnosis. Combining FTO, PIK3CB, CEA and CA15-3 improves the diagnostic efficiency of breast cancer.

Somatic genomic imbalances in 'tumour-free' surgical margins of oral cancer

Up to 30% of oral squamous cell carcinoma (OSCC) patients develop local recurrence and distant metastasis. The molecular status of histologically cancer-free tumour margins could be a critical factor in predicting tumour behaviour. The aim of this study was to detect somatic genomic imbalances in OSCC with emphasis on the surgical margins. DNA was isolated from tumour tissues, margin tissues, and blood samples (used as control) obtained from 11 OSCC patients, and genome-wide array comparative genomic hybridization was performed. Imbalances were present in both tumours and margins, although, as expected, they were more prevalent in tumours (duplications, P = 0.0002; deletions, P = 0.0001). Duplications were more frequent than deletions in both tumours and margins, but without statistical significance. Fifteen imbalances in tumour tissues were recurrent and all of them were duplications. Four of these were found both in tumours and margins and involved chromosomes 1q, 8p, Xp, Yp, and Yq. Four imbalances were recurrent in margin tissue and all of them were duplications (autosomes 8 and 17 and both sex chromosomes). Histologically 'cancer-free' margins hide genomic alterations consistent with unexplained OSCC recurrences. Establishing the molecular status of the margins could improve outcome prediction.

Identification of a Novel Gene Signature with DDR and EMT Difunctionalities for Predicting Prognosis, Immune Activity, and Drug Response in Breast Cancer

Breast cancer, with an overall poor clinical prognosis, is one of the most heterogeneous cancers. DNA damage repair (DDR) and epithelial-mesenchymal transition (EMT) have been identified to be associated with cancer's progression. Our study aimed to explore whether genes with both functions play a more crucial role in the prognosis, immune, and therapy response of breast cancer patients. Based on the Cancer Genome Atlas (TCGA) cancer database, we used LASSO regression analysis to identify the six prognostic-related genes with both DDR and EMT functions, including TP63, YWHAZ, BRCA1, CCND2, YWHAG, and HIPK2. Based on the six genes, we defined the risk scores of the patients and reasonably analyzed the overall survival rate between the patients with the different risk scores. We found that overall survival in higher-risk-score patients was lower than in lower-risk-score patients. Subsequently, further GO and KEGG analyses for patients revealed that the levels of immune infiltration varied for patients with high and low risk scores, and the high-risk-score patients had lower immune infiltration's levels and were insensitive to treatment with chemotherapeutic agents. Furthermore, the Gene Expression Omnibus (GEO) database validated our findings. Our data suggest that TP63, YWHAZ, BRCA1, CCND2, YWHAG, and HIPK2 can be potential genetic markers of prognostic assessment, immune infiltration and chemotherapeutic drug sensitivity in breast cancer patients.

The oncogenic driving force of CD30 signaling-induced chromosomal instability in adult T-cell leukemia/lymphoma

Adult T-cell leukemia/lymphoma (ATL) develops via stepwise accumulation of gene mutations and chromosome aberrations. However, the molecular mechanisms underlying this tumorigenic process are poorly understood. We previously reported the presence of a biological link between the expression of CD30, which serves as a marker for ATL progression, and the actively proliferating fraction of human T-cell leukemia virus type 1 (HTLV-1)-infected cells that display polylobulation. Here, we demonstrated that CD30 signaling induced chromosomal instability with clonal expansion through DNA double-strand breaks (DSBs) via an increase of intracellular reactive oxygen species. CD30⁺ ATL cells were composed of subclones with additional genomic aberrations compared with CD30^- ATL cells in ATL patients. Furthermore, we found an accumulation of copy number loss of DSB repair-related genes as the disease progressed. Taken together, CD30 expression on ATL cells appears to be correlated with genomic instability, suggesting that CD30 signaling is one of the oncogenic factors of ATL progression with clonal evolution. This study provides new insight into the biological roles of CD30 signaling and could improve our understanding of tumorigenic processes of HTLV-1-infected cells.

Prognostic signature related to the immune environment of oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) prognosis remains poor. Here we aimed to identify an effective prognostic signature for predicting the survival of patients with OSCC. Gene-expression and clinical data were obtained from the Cancer Genome Atlas database. Immune microenvironment-associated genes were identified using bioinformatics. Subtype and risk-score analyses were performed for these genes. Kaplan–Meier analysis and immune cell infiltration level were explored in different subtypes and risk-score groups. The prognostic ability, independent prognosis, and clinical features of the risk score were assessed. Furthermore, immunotherapy response based on the risk score was explored. Finally, a conjoint analysis of the subtype and risk-score groups was performed to determine the best prognostic combination. We found 11 potential prognostic genes and constructed a risk-score model. The subtype cluster 2 and a high-risk group showed the worst overall survival; differences in survival status might be due to the different immune cell infiltration levels. The risk score showed good performance, independent prognostic value, and valuable clinical application. Higher risk scores showed higher Tumor Immune Dysfunction and Exclusion scores, indicating that patients with a high-risk score were less likely to benefit from immunotherapy. Finally, conjoint analysis for the subgroups and risk groups showed the best predictive ability.

Integrated Multi-Omics Signature Predicts Survival in Head and Neck Cancer

Head and Neck Cancer (HNC) is characterized by phenotypic, biological, and clinical heterogeneity. Despite treatment modalities, approximately half of all patients will die of the disease. Several molecular biomarkers have been investigated, but until now, without clinical translation. Here, we identified an integrative nine-gene multi-omics signature correlated with HNC patients’ survival independently of relapses or metastasis development. This prognosis multi-omic signature comprises genes mapped in the chromosomes 1q, 3p, 8q, 17q, 19p, and 19q and encompasses alterations at copy number, gene expression, and methylation. Copy number alterations in LMCD1-A1S and GRM7, the methylation status of CEACAM19, KRT17, and ST18, and the expression profile of RPL29, UBA7, FCGR2C, and RPSAP58 can predict the HNC patients’ survival. The difference higher than two years observed in the survival of HNC patients that harbor this nine-gene multi-omics signature can represent a significant step forward to improve patients’ management and guide new therapeutic targets development.

A Novel Immune-Related Gene Signature to Identify the Tumor Microenvironment and Prognose Disease Among Patients With Oral Squamous Cell Carcinoma Patients Using ssGSEA: A Bioinformatics and Biological Validation Study

Oral squamous cell carcinoma (OSCC) is the most invasive oral malignancy in adults and is associated with a poor prognosis. Accurate prognostic models are urgently needed, however, knowledge of the probable mechanisms behind OSCC tumorigenesis and prognosis remain limited. The clinical importance of the interplay between the immune system and tumor microenvironment has become increasingly evident. This study explored immune-related alterations at the multi-omics level to extract accurate prognostic markers linked to the immune response and presents a more accurate landscape of the immune genomic map during OSCC. The Cancer Genome Atlas (TCGA) OSCC cohort (n = 329) was used to detect the immune infiltration pattern of OSCC and categorize patients into two immunity groups using single-sample gene set enrichment analysis (ssGSEA) and hierarchical clustering analysis. Multiple strategies, including lasso regression (LASSO), Cox proportional hazards regression, and principal component analysis (PCA) were used to screen clinically significant signatures and identify an incorporated prognosis model with robust discriminative power on the survival status of both the training and testing set. We identified two OSCC subtypes based on immunological characteristics: Immunity-high and immunity low, and verified that the categorization was accurate and repeatable. Immunity_ high cluster with a higher immunological and stromal score. 1047 differential genes (DEGs) integrate with immune genes to obtain 319 immue-related DEGs. A robust model with five signatures for OSCC patient prognosis was established. The GEO cohort (n = 97) were used to validate the risk model’s predictive value. The low-risk group had a better overall survival (OS) than the high-risk group. Significant prognostic potential for OSCC patients was found using ROC analysis and immune checkpoint gene expression was lower in the low-risk group. We also investigated at the therapeutic sensitivity of a number of frequently used chemotherapeutic drugs in patients with various risk factors. The underlying biological behavior of the OSCC cell line was preliminarily validated. This study characterizes a reliable marker of OSCC disease progression and provides a new potential target for immunotherapy against this disease.

Evaluation of the Prognostic Relevance of Differential Claudin Gene Expression Highlights Claudin-4 as Being Suppressed by TGFβ1 Inhibitor in Colorectal Cancer

Background: Claudins (CLDNs) are a family of closely related transmembrane proteins that have been linked to oncogenic transformation and metastasis across a range of cancers, suggesting that they may be valuable diagnostic and/or prognostic biomarkers that can be used to evaluate patient outcomes. However, CLDN expression patterns associated with colorectal cancer (CRC) remain to be defined.

Methods: The mRNA levels of 21 different CLDN family genes were assessed across 20 tumor types using the Oncomine database. Correlations between these genes and patient clinical outcomes, immune cell infiltration, clinicopathological staging, lymph node metastasis, and mutational status were analyzed using the GEPIA, UALCAN, Human Protein Atlas, Tumor Immune Estimation Resource, STRING, Genenetwork, cBioportal, and DAVID databases in an effort to clarify the potential functional roles of different CLDN protein in CRC. Molecular docking analyses were used to probe potential interactions between CLDN4 and TGFβ1. Levels of CLDN4 and CLDN11 mRNA expression in clinical CRC patient samples and in the HT29 and HCT116 cell lines were assessed via qPCR. CLDN4 expression levels in these 2 cell lines were additionally assessed following TGFβ1 inhibitor treatment.

Results: These analyses revealed that COAD and READ tissues exhibited the upregulation of CLDN1, CLDN2, CLDN3, CLDN4, CLDN7, and CLDN12 as well as the downregulation of CLDN5 and CLDN11 relative to control tissues. Higher CLDN11 and CLDN14 expression as well as lower CLDN23 mRNA levels were associated with poorer overall survival (OS) outcomes. Moreover, CLDN2 and CLDN3 or CLDN11 mRNA levels were significantly associated with lymph node metastatic progression in COAD or READ lower in COAD and READ tissues. A positive correlation between the expression of CLDN11 and predicted macrophage, dendritic cell, and CD4+ T cell infiltration was identified in CRC, with CLDN12 expression further being positively correlated with CD4+ T cell infiltration whereas a negative correlation was observed between such infiltration and the expression of CLDN3 and CLDN15. A positive correlation between CLDN1, CLDN16, and neutrophil infiltration was additionally detected, whereas neutrophil levels were negatively correlated with the expression of CLDN3 and CLDN15. Molecular docking suggested that CLDN4 was able to directly bind via hydrogen bond with TGFβ1. Relative to paracancerous tissues, clinical CRC tumor tissue samples exhibited CLDN4 and CLDN11 upregulation and downregulation, respectively. LY364947 was able to suppress the expression of CLDN4 in both the HT29 and HCT116 cell lines.

Conclusion: Together, these results suggest that the expression of different CLDN family genes is closely associated with CRC tumor clinicopathological staging and immune cell infiltration. Moreover, CLDN4 expression is closely associated with TGFβ1 in CRC, suggesting that it and other CLDN family members may represent viable targets for antitumor therapeutic intervention.

ImaGene: a web-based software platform for tumor radiogenomic evaluation and reporting

Summary

Radiographic imaging techniques provide insight into the imaging features of tumor regions of interest, while immunohistochemistry and sequencing techniques performed on biopsy samples yield omics data. Relationships between tumor genotype and phenotype can be identified from these data through traditional correlation analyses and artificial intelligence (AI) models. However, the radiogenomics community lacks a unified software platform with which to conduct such analyses in a reproducible manner. To address this gap, we developed ImaGene, a web-based platform that takes tumor omics and imaging datasets as inputs, performs correlation analysis between them, and constructs AI models. ImaGene has several modifiable configuration parameters and produces a report displaying model diagnostics. To demonstrate the utility of ImaGene, we utilized data for invasive breast carcinoma (IBC) and head and neck squamous cell carcinoma (HNSCC) and identified potential associations between imaging features and nine genes (WT1, LGI3, SP7, DSG1, ORM1, CLDN10, CST1, SMTNL2, and SLC22A31) for IBC and eight genes (NR0B1, PLA2G2A, MAL, CLDN16, PRDM14, VRTN, LRRN1, and MECOM) for HNSCC. ImaGene has the potential to become a standard platform for radiogenomic tumor analyses due to its ease of use, flexibility, and reproducibility, playing a central role in the establishment of an emerging radiogenomic knowledge base.

Availability and implementation

www.ImaGene.pgxguide.org, https://github.com/skr1/Imagene.git.

Supplementary information

Supplementary data are available at https://github.com/skr1/Imagene.git.

Screening and cellular validation of prognostic genes regulated by super enhancers in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) is the leading cause of death in patients with head and neck cancer. Reliable biomarkers to guide treatment decisions for OSCC remain scarce. The purpose of this study was to identify novel prognostic markers regulated by super enhancers in OSCC. Eight modules were obtained by weighted gene co-expression network analysis (WGCNA), among which MEblue module had the highest correlation with tumor stage, alcohol consumption and smoking. There were 41 genes regulated by super enhancers in MEblue module. Functional analysis showed that 41 super enhancer-regulated genes were involved in cancer progression. A total of twenty transcription factors of the 41 genes were predicted. Prognostic analysis of the 41 genes and the top 5 transcription factors showed that patients with high expression of AHCY, KCMF1, MANBAL and TFDP1 had a poor prognosis. Immunohistochemical analysis showed that AHCY, KCMF1 and MANBAL were highly expressed in OSCC tissue. Cellular experiment demonstrated that TFDP1 promoted AHCY, KCMF1 and MANBAL expression by binding to the super enhancers of these genes. Knockdown of TFDP1, AHCY, KCMF1 and MANBAL inhibited the proliferation of OSCC cells. In conclusion, AHCY, KCMF1 and MANBAL were recognized as super enhancer-regulated prognostic biomarkers regulated by TFDP1 in OSCC.