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Identifying non-invasive blood-based biomarkers is crucial for early detection and monitoring of liver cancer (LC), thereby improving patient outcomes. This study leveraged computational approaches to predict potential blood-based biomarkers for LC. Machine learning (ML) models were developed using selected features from blood-secretory proteins collected from the curated databases. The logistic regression (LR) model demonstrated the optimal performance. Transcriptome analysis across 7 LC cohorts revealed 231 common differentially expressed genes (DEGs). The encoded proteins of these DEGs were compared with the ML dataset, revealing 29 proteins overlapping with the blood-secretory dataset. The LR model also predicted 29 additional proteins as blood-secretory with the remaining protein-coding genes. As a result, 58 potential blood-secretory proteins were obtained. Among the top 20 genes, 13 common hub genes were identified. Further, area under the receiver operating characteristic curve (ROC AUC) analysis was performed to assess the genes as potential diagnostic blood biomarkers. Six genes, ESM1, FCN2, MDK, GPC3, CTHRC1 and COL6A6, exhibited an AUC value higher than 0.85 and were predicted as blood-secretory. This study highlights the potential of an integrative computational approach for discovering non-invasive blood-based biomarkers in LC, facilitating for further validation and clinical translation. SIGNIFICANCE: Liver cancer is one of the leading causes of premature death worldwide, with its prevalence and mortality rates projected to increase. Although current diagnostic methods are highly sensitive, they are invasive and unsuitable for repeated testing. Blood biomarkers offer a promising non-invasive alternative, but their wide dynamic range of protein concentration poses experimental challenges. Therefore, utilizing available omics data to develop a diagnostic model could provide a potential solution for accurate diagnosis. This study developed a computational method integrating machine learning and bioinformatics analysis to identify potential blood biomarkers. As a result, ESM1, FCN2, MDK, GPC3, CTHRC1 and COL6A6 biomarkers were identified, holding significant promise for improving diagnosis and understanding of liver cancer. The integrated method can be applied to other cancers, offering a possible solution for early detection and improved patient outcomes., Competing Interests: Declaration of competing interest The authors declare they have no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)

Endoplasmic reticulum stress may affect the occurrence and development of cancer. However, its effect on the prognosis of colon cancer (CC) patients is not clear yet. Herein, based on TCGA database, we screened 15 endoplasmic reticulum stress responsive genes (ERSRGs) associated with the prognosis of CC patients by Cox regression. By LASSO and multivariate Cox regression analyses, a prognostic risk assessment model involving 12 genes (DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, GRIN2B, LRRC59, and RORC) was built. The survival curves indicated that patients in the low-risk group had good prognosis. ROC curves demonstrated a good performance of this 12-gene prognostic model, and the Riskscore could be considered as an independent prognostic factor. Patients in low-risk group benefit more from immune checkpoint inhibitor and immune checkpoint blockade (ICB) treatment. Besides, the enrichment analysis suggested a remarkable difference in Ca 2+ signaling in both groups. Finally, based on the cMAP database, we identified several potential drugs that could target high-risk groups, such as Dasatinib, GNF-2, Saracatinib, and WZ-1-84. To sum up, our research constructed an ERSRGs-characteristic prognostic model. The model is a promising biomarker for prediction of clinical outcomes and immune therapy response of CC patients. SIGNIFICANCE: Based on the transcriptomic data of colon cancer in the TCGA database, this study screens 12 endoplasmic reticulum stress-related genes (ERSRGs), including DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, asphD1, NTRK2. GRIN2B, LRRC59, and RORC, and a prognostic model was constructed. This model can be used as a predictor of prognosis and immunotherapy response in colon cancer patients. At the same time, model-based prediction of drugs can also be a potential option for colon cancer treatment in the future., Competing Interests: Declaration of competing interest The authors declares that this article does not present any conflict of interest., (Copyright © 2024. Published by Elsevier B.V.)

The somatic BRCA1 or BRCA2 Pathogenic Variant (PV)/Likely PV (LPV) from Next Generation Sequencing (NGS) is the most important biomarker for PARP inhibitor use and maintenance-targeted therapies. A discrepancy in the detection rates of BRCA1 and BRCA2 PV/LPV was identified among the NGS platforms. The objective of this study was to compare the somatic BRCA results from two distinct platforms using the same cohort and to identify the causes of these differences. Patients with epithelial ovarian cancer who concurrently underwent tumor NGS using two different platforms between January 2022 and June 2023 were included in this study. The two platforms used were in-house tumor NGS (Illumina NextSeq 550Dx, SureSelectXT library kit, and datasets from 1000 Genomes, ESP6500, ExAC, and ClinVar) and GreenPlan homologous recombination deficiency (HRD) test (Illumina NextSeq 550Dx, customized Twist Bioscience library kit, and datasets from COSMIC and OncoKB). The results of somatic mutations in BRCA1 and BRCA2 were compared between the two platforms. Of the 118 patients, 11.9% (n = 14) exhibited a discordant interpretation of BRCA1 or BRCA2 between the two platforms. Eleven patients (9.3%) exhibited negative results in the in-house platform but positive results (eight seven as PV of BRCA1, one as PV of BRCA2, one as LPV of BRCA1, and two as LPV of BRCA2) in the GreenPlan HRD test, while three patients (2.6%) had positive BRCA pathogenic variants (two as PV of BRCA1 [c.3340G > T, c.5152 + 3 A > C], one as LPV of BRCA2 [c.8174G > T], and one as LPV of BRCA1 [c.5017_5019delCAC]) in the in-house platform but a negative result in the GreenPlan HRD test. The discordance rate of somatic BRCA1 or BRCA2 mutations from different platforms was approximately 12%. In the case of the strong implication of BRCA PV/LPV with a negative result with one genetic test, different platforms could be considered in limited cases. Careful interpretation and further studies for the cross-validation of gene analysis platforms are needed., (© 2024. The Author(s).)

The most well-studied epigenetic marker in humans is the 5-methyl modification of cytosine in DNA, which has great potential as a disease biomarker. Currently, quantification of DNA methylation relies heavily on bisulfite conversion followed by PCR amplification and NGS or microarray analysis. PCR is subject to potential bias in differential amplification of bisulfite-converted methylated versus unmethylated sequences. Here, we combine bisulfite conversion with single-molecule kinetic fingerprinting to develop an amplification-free assay for DNA methylation at the branched-chain amino acid transaminase 1 (BCAT1) promoter. Our assay selectively responds to methylated sequences with a limit of detection below 1 fM and a specificity of 99.9999%. Evaluating complex genomic DNA matrices, we reliably distinguish <5% DNA methylation at the BCAT1 promoter in whole blood DNA from completely unmethylated whole-genome amplified DNA. Taken together, these results demonstrate the feasibility and sensitivity of our amplification-free, single-molecule quantification approach to improve the early detection of methylated cancer DNA biomarkers.

Acute myeloid leukemia (AML) is a malignant tumor with high recurrence and refractory rates and low survival rates. Increased glycolysis is characteristic of metabolism in AML blast cells and is also associated with chemotherapy resistance. The purpose of this study was to use gene expression and clinical information from The Cancer Genome Atlas (TCGA) database to identify subtypes of AML associated with lactate metabolism. Two different subtypes linked to lactate metabolism, each with specific immunological features and consequences for prognosis, were identified in this study. Using the TCGA and International Cancer Genome Consortium (GEO) cohorts, a prognostic model composed of genes (LMNA, RETN and HK1) for the prognostic value of the lactate metabolism-related risk score prognostic model was created and validated, suggesting possible therapeutic uses. Additionally, the diagnostic value of the prognostic model genes was explored. LMNA and HK1 were ultimately identified as hub genes, and their roles in AML were determined through immune infiltration, GeneMANIA, GSEA, methylation analysis and single-cell analysis. LMNA was upregulated in AML associating with a poor prognosis while HK1 was downregulated in AML associating with a favorable prognosis. The findings underscore the noteworthy impact of genes linked to lactate metabolism in AML and illustrate the possible therapeutic usefulness of the lactate metabolism-related risk score and the hub lactate metabolism-related genes in guiding AML patients' treatment choices., (© 2024. The Author(s).)

Objective: To explore the medical significance of methylated septin9 (mSEPT9) in monitoring recurrence and prognostic assessment in individuals with surgically treated colorectal cancer (CRC)., Methods: To investigate the role of Septin9 in colorectal cancer, we utilized the TIMER2.0 database to analyze its differential expression between tumor tissues and adjacent normal tissues. Colorectal cancer RNA-seq data from the TCGA database was downloaded and curated. The clinical relevance of mSEPT9 in colorectal cancer was explored by examining the correlation between Septin9 methylation levels and clinical characteristics using UALCAN and MethSurv software. Peripheral blood samples were obtained from 130 CRC subjects who underwent surgery for the detection of mSEPT9 and carcinoembryonic antigen (CEA) expression, along with collection of clinicopathological data such as age, gender, tumor site, TNM stage, and tumor differentiation. Patients were followed up for at least 3 years post-surgery until the death or final follow-up dates (31/12/2022). Additionally, peripheral blood samples were collected from 30 colorectal cancer surgery patients for mSEPT9 detection before and 7 days after surgery., Results: Through bioinformatic database analysis, we identified higher expression levels of SEPT9 mRNA in most tumor tissues compared to normal tissues. Similarly, both paired and unpaired CRC tissues exhibited elevated expression of Septin9 when compared to normal tissues. Following GO and KEGG analysis of Septin9 target genes, we discovered their significant associations with ncRNA metabolic processes, ribonucleoprotein complex biogenesis, spliceosomes, and viral carcinogenesis. Furthermore, the overexpression of mSeptin9 was observed in CRC tissues, and it demonstrated a correlation with colon cancer staging and histologic classification. In our clinical sample study, The positive rate of mSEPT9 in CRC patients 7 days after surgery was 43.44% lower than that of preoperative. The differences in TNM stage, tumor differentiation degree, and preoperative CEA expression level between the preoperative mSEPT9 positive and negative groups of CRC were statistically significant (P < 0.05). Recurrence free survival (RFS) and overall survival (OS) were shorter in the preoperative mSEPT9-positive group, meaning preoperative mSEPT9 status was a risk factor for CRC recurrence and prognosis (P < 0.05). The sensitivity, specificity, and AUC value of preoperative mSEPT9 and CEA levels for predicting postoperative recurrence in CRC patients were 88% vs. 72%, 56.19% vs. 55.24%, and 0.721 vs. 0.636 respectively, well the AUC value of the combined prediction of postoperative recurrence was 0.758., Conclusion: The detection of mSEPT9 combined with CEA in preoperative plasma helps predict recurrence in colorectal cancer patients., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Li et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. This study was aimed to identify a lipid metabolism-related signature associated with the HCC microenvironment to improve the prognostic prediction of HCC patients. Clinical information and expression profile data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, including the GEO dataset GSE76427. The gene expression profile of lipid metabolism was downloaded from Molecular Signatures Database (MSigDB) database. The infiltrating immune cells were estimated by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE), MCP-counter, and TIMER algorithms. Functional analysis, including Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) were performed to elucidate the underlying mechanisms. The prognostic risk model was performed by Least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression analysis. Two distinct subgroups of survival were identified. Better prognosis was associated with high immune score, high abundance of immune infiltrating cells, and high immune status. GO and KEGG analysis showed that differentially expressed genes (DEGs) between the two subgroups were mainly enriched in immune related pathways. GSEA analysis suggested that the expression of lipid metabolism related genes (LMRGs) was related to dysregulation of immune in the high-risk group. Risk models and clinical features based on LMRGs predicted HCC prognosis. This study indicated that the lipid metabolism-related signature was important for the prognosis of HCC. The expression of LMRGs was related to the immune microenvironment of HCC patients and could be used to predict the prognosis of HCC., (© 2024. The Author(s).)

Increasing evidence highlights the important role of ubiquitination in cancer. The objective of our study is to establish a reliable marker for predicting clinical outcomes and treatment responses in patients with clear cell renal cell carcinoma (ccRCC) using genes related to ubiquitination (URGs). The URGs subtypes were identified using consensus clustering based on TCGA-KIRC, and a signature containing the prognostic differentially expressed genes of the subtypes was determined using LASSO and Cox regression analysis. To demonstrate the strength of the signature, verification analyses were performed on both E-MTAB-1980 and TCGA-KIRC test datasets. We developed a nomogram to enhance the effectiveness of our predictive tool. Risk genes expression was determined through RT-qPCR. Six genes were combined to create the URGs signature, which had a highly correlated with patient prognosis in patients with ccRCC. A nomogram was developed based on the URGs signature and clinicopathological characteristics. We found that the predictive power was substantially greater than the other individual predictors. Moreover, the study on the immune microenvironment revealed significant variations in the levels of immune cells and the expression of immune checkpoint genes among the groups categorized as high-risk and low-risk. Furthermore, it was found that immunotherapy yielded better outcomes in cohorts with low risk. The URGs signature might serve as a novel and powerful prognosis biomarker and offer a momentous reference for individualized treatment for patients in ccRCC., (© 2024. The Author(s).)

Esophageal squamous cell carcinoma (ESCC) is a prevalent malignancy within the digestive system, characterized by high incidence and mortality rates. The biological role of REEP5 in ESCC progression remains poorly understood, despite its associations with various diseases, potentially accelerating tumor malignancy. We retrieved RNA-seq data and clinical information from 179 ESCC patients from the Gene Expression Omnibus (GEO) and 93 patients from The Cancer Genome Atlas (TCGA) databases. Bioinformatics analyses were conducted to explore the biological functions of REEP5 in ESCC, its role in the tumor microenvironment, and its prognostic value. Additionally, utilizing single-cell RNA-seq (scRNA-seq) data from 3 ESCC patients in the GEO database, we performed cluster analyses to investigate cell-specific expression differences of REEP5 between cancerous and adjacent non-cancerous tissues. Molecular biology experiments were also conducted to validate REEP5 expression disparities between tumor and non-tumor tissues. Compared to normal tissues, REEP5 was significantly enriched in ESCC tissues. High REEP5 expression was closely associated with poor prognosis in ESCC patients. Gene Ontology (GO) analysis revealed strong correlations between REEP5 and processes such as mRNA splicing and protein stabilization. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) indicated positive correlations between REEP5 and mRNA spliceosome assembly and disassembly. Pearson correlation analysis demonstrated positive associations between REEP5 and cancer-inhibitory immune checkpoints CTLA-4, TIM-3, and HVEM. Single-cell clustering and CIBERSORT analysis showed that REEP5 expression was closely related to T-cell infiltration in ESCC, with significant enrichment effects observed in CD8+ T-cell infiltration. REEP5 expression is closely correlated with the pathological and molecular pathology of ESCC, potentially playing a crucial role in Mast cell or T-cell-mediated immune responses in ESCC. Therefore, REEP5 holds promise as a novel therapeutic target for ESCC., (© 2024. The Author(s).)

Cervical cancer (CC) was considered to be the most common gynaecological cancer, with an estimated 342,000 deaths worldwide each year, as the majority of patients were diagnosed at an advanced stage of the disease. The purpose of this study was to evaluate the predictive value of multi-locus methylation assay for the early detection of CC. The cervical exfoliated cell samples from 492 HPV-positive females with cervical lesions were collected and subjected to methylation detection of gene FAM19A4, EPB41L3 and PAX1 after bisulfite conversion. The levels of gene methylation in patients with different severity of cervical lesions were evaluated and compared. The receiver-operating characteristic (ROC) curve was established and efficacy indexes such as sensitivity, specificity and area under the curve (AUC) were calculated to assess the diagnostic value of DNA methylation detection at multiple gene loci for CC. The methylation levels of FAM19A4, EPB41L3 and PAX1 were significantly increased with the grade of cervical squamous intraepithelial lesions. The sensitivities of FAM19A4, EPB41L3 and PAX1 alone for high-grade squamous intraepithelial lesion (HSIL) and CC diagnosis were 84.6%, 86.3% and 88.0%, respectively; when three markers were combined by a logistic regression model, the sensitivity was 88.0%, with a high specificity of 97.7% and AUC of 0.957 (95% CI 0.937-0.977). Methylation status of FAM19A4, EPB41L3 and PAX1 were highly specific and effective for monitoring the progression of cervical lesions and the tri-gene methylation assay could be used as a triage tool for CC early screening., (© 2024. The Author(s).)

Osteosarcoma (OS) is a cancerous tumor, and its development is greatly influenced by long non-coding RNA (lncRNA). Endoplasmic reticulum stress (ERS) is an essential biological defense process in cells and contributes to the progression of tumors. However, the exact mechanisms remain elusive. This study aims to develop a signature of lncRNAs associated with ERS in OS. This signature will guide the prognosis prediction and the determination of appropriate treatment strategies. The UCSC Xena database collected transcriptional and clinical data of OS and muscle, after identifying ERS differentially expressed genes, we utilized correlation analysis to determine the endoplasmic reticulum stress lncRNAs (ERLs). The Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analysis were utilized to develop an ERLs signature. To clarify the fundamental mechanisms controlling gene expression in low and high-risk groups, Gene Set Variation Analysis (GSVA) were conducted. In addition, the distinction between the two groups regarding drug sensitivity and immune-related activity was investigated to determine the immunotherapy effects. Utilizing RT-qPCR, the expression of model lncRNAs in OS cell lines was ascertained. The functional analysis of LINC02298 was carried out through in vitro experiments and pan-cancer analysis. This study successfully constructed an ERLs prognostic signature for OS, which comprised 5 lncRNAs (AC023157.3, AL031673.1, LINC02298, LINC02328, SNHG26). The risk signature predicted overall survival in patients with OS and was confirmed by assessing the validation and whole cohorts. Further, it was discovered that individuals classified as high-risk displayed suppressed immune activation, decreased infiltration of immune cells, and decreased responsiveness to immunotherapy. The RT-qPCR showed that the constructed risk prognosis model is reliable. Experimental validation has demonstrated that LINC02298 can promote OS cells' invasion, migration, and proliferation. In addition, LINC02298 exhibited significant differential expression in many types of cancer. Moreover, LINC02298 is an important biomarker in a variety of tumors. This study established a novel ERLs signature, which successfully predicted the prognosis of OS. The function of LINC02298 in OS was elucidated via in vitro experiments. Therefore, it offers new opportunities for predicting the clinical prognosis of OS and establishes the basis for targeted therapy in OS., (© 2024. The Author(s).)

Domestic dogs (Canis lupus familiaris) serve as valuable translational models for human cancer research due to their biological similarities. Canine mammary tumors (CMTs), frequently diagnosed in female dogs, share various characteristics with human breast cancers. This study investigates the PIK3CA (H1047R) mutation in CMTs using droplet digital PCR (ddPCR) and explores the potential of liquid biopsy for non-invasive detection. We analyzed 80 formalin-fixed, paraffin-embedded (FFPE) CMT tissue samples and compared ddPCR results with next-generation sequencing (NGS) data, achieving high concordance. Plasma and serum samples were also assessed for mutation concordance with tissue results. Our findings indicate a higher frequency of the PIK3CA (H1047R) mutations in benign and grade I malignant CMTs compared to more aggressive malignancies. The ddPCR assay demonstrated high sensitivity and specificity, with plasma testing showing 78.6% sensitivity and 87.5% specificity, and serum testing showing 66.7% sensitivity and 90.0% specificity. These results highlight the viability of liquid biopsy as a minimally invasive method for monitoring PIK3CA mutations in canine patients. The study suggests that liquid biopsy techniques hold significant promise for improving the early detection and monitoring of canine cancers, warranting further research to refine these methods and explore their applications in canine cancer diagnostics and treatment., (© 2024. The Author(s).)

Heterogeneous behavior of each cell type and their cross-talks in tumor immune microenvironment (TIME) refers to tumor immunological heterogeneity that emerges during tumor progression and represents formidable challenges for effective anti-tumor immune response and promotes drug resistance. To comprehensively elucidate the heterogeneous behavior of individual cell types and their interactions across different stages of tumor development at system level, a computational framework was devised that integrates cell specific data from single-cell RNASeq into networks illustrating interactions among signaling and metabolic response genes within and between cells in TIME. This study identified stage specific novel markers which remodel the cross-talks, thereby facilitating immune stimulation. Particularly, multicellular knockout of metabolic gene APOE (Apolipoprotein E in mast cell, myeloid cell and fibroblast) combined with signaling gene CAV1 (Caveolin1 in endothelial and epithelial cells) resulted in the activation of T-cell mediated signaling pathways. Additionally, this knockout also initiated intervention of cytotoxic gene regulations during tumor immune cell interactions at the early stage of Lung Adenocarcinoma (LUAD). Furthermore, a unique interaction motif from multiple cells emerged significant in regulating the overall immune response at the advanced stage of LUAD. Most significantly, FCER1G (Fc Fragment of IgE Receptor Ig) was identified as the common regulator in activating the anti-tumor immune response at both stages. Predicted markers exhibited significant association with patient overall survival in patient specific dataset. This study uncovers the significance of signaling and metabolic interplay within TIME and discovers important targets to enhance anti-tumor immune response at each stage of tumor development., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Purpose: MYB has been shown to play a central role in oncogenesis in a majority of adenoid cystic carcinomas (ACC). Testing for MYB expression via immunohistochemistry (IHC) or testing for the MYB gene fusion by next-generation sequencing (NGS) have become useful tools for the diagnosis of ACC. In addition, detection of MYB expression may have implications for patient management., Methods: A cohort of 35 ACC cases was identified from the archival pathology files of the Massachusetts General Hospital. Cases were tested for MYB expression using a panel of 4 different commercially available MYB antibodies and scored using a modified Allred system. RNA-based NGS for MYB gene fusion detection was also performed., Results: Among 4 different MYB antibodies, the sensitivity for MYB detection ranged from 26 to 97%. When a 30% threshold for determination of MYB immunohistochemical positivity was used, the AB&#95;10900735 IHC clone showed the maximum sensitivity (97%). RNA sequencing revealed 19 (54%) cases positive for MYB fusions, and expression analysis derived from the sequencing data confirmed a significant association between MYB expression and fusion status (p = 0.036). Although less sensitive, the AB&#95;778878 MYB clone showed a significant positive association between IHC staining and MYB RNA expression (R 2  = 0.15, p = 0.023)., Conclusion: The detection of MYB expression using immunohistochemistry varies significantly depending on the antibody used. Comparison with MYB fusion and transcription levels, as determined by NGS, reveals that MYB has a complex relationship between genetic alterations, transcript levels, and protein abundance., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Ovarian cancer (OC) has a limited immunotherapeutic response; hence, this study aimed to investigate the relationship between CXC-chemokine ligand 13 (CXCL13) expression and overall survival (OS) rate, key immune pathways, degree of immune cell infiltration, and progressive disease (PD)-1 checkpoint blockade. A total of 703 differentially expressed genes were obtained from "The Cancer Genome Atlas" (TCGA) database based on the immune and stromal scores of 379 OC patients for getting the targeted gene CXCL13. The association between CXCL13 and OS in OC patients, biological function annotation of CXCL13, and its correlation with immune components were assessed. The results indicated that upregulated CXCL13 expression was positively correlated with better OC patient prognosis. CXCL13 expression was associated with 6 immune-related pathways, 10 immune cells, and PD-1 expression of OC micro-environment. Moreover, high expression of CXCL13 was related to a better tumor response and more extended tumor-stable stage after PD-1 blocking therapy in IMvigor210. The study concluded that CXCL13 could be a prognostic marker and a potential immunotherapy target for OC patients, especially PD-1 checkpoint blockade., Competing Interests: All authors declare that they have no conflict of interests., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths globally, with limited treatment options. The goal of this study was to use integrated bioinformatic analysis to find possible biomarkers for prognosis and therapeutic targets for hepatitis B (HBV)-associated HCC. Three microarray datasets (GSE84402, GSE121248, and E-GEOD-19665) from patients with HBV-associated HCC were combined and analyzed. We identified differentially expressed genes (DEGs) and performed pathway enrichment analysis. We constructed protein-protein interaction networks to identify hub genes. We identified a total of 374 DEGs, which included 90 up-regulated and 284 down-regulated genes. Pathway enrichment analysis revealed associations with cell cycle, oocyte meiosis, and the p53 signaling pathway for up-regulated DEGs. Twenty hub genes were identified, and 9 of them (ZWINT, MELK, DLGAP5, BIRC5, AURKA, HMMR, CDK1, TTK, and MAD2L1) were validated using the Cancer Genome Atlas data and Kaplan-Meier survival analysis. These genes were significantly associated with a poor prognosis in HCC patients. Our research shows that ZWINT, MELK, DLGAP5, BIRC5, AURKA, HMMR, CDK1, TTK, and MAD2L1 may be useful for predicting how HBV-associated HCC will progress and for finding new ways to treat it. In addition to these further studies are needed to elucidate the functions of the remaining 11 identified hub genes (RRM2, NUSAP1, PBK, CCNB1, CCNB2, BUB1B, NEK2, CENPF, ASPM, TOP2A, and BUB1) in HCC development and progression., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Aggressive clear cell renal cell carcinoma (ccRCC) has a bad prognosis. We seek new ccRCC biomarkers for diagnosis and treatment. We used exoRBase and The Cancer Genome Atlas Database to compare DEmRNAs, DEmiRNAs, DElncRNAs, and DEcircRNAs in ccRCC and normal renal tissues. CircRNAs and circRNAs targeting microRNAs (miRNAs) were anticipated and taken intersections, and several databases assessed the targeted link between common miRNAs and messenger RNAs (mRNAs). The Cancer Genome Atlas database was used to create a predictive mRNA signature that was validated in E-MTAB-1980. Finally, we examined competing endogenous RNA network miRNAs and long noncoding RNAs for ccRCC predictive biomarkers using overall survival analysis. We built the first competing endogenous RNA regulation network of circRNA-lncRNA-miRNA-mRNA and found that it substantially correlates with ccRCC prognosis. We unveiled ccRCC's posttranscriptional regulation mechanism in greater detail. Our findings identified novel biomarkers for ccRCC diagnosis, therapy, and prognosis., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: New diagnostic tools are needed to improve the diagnosis and risk stratification of cutaneous melanoma. Disease-specific microRNA signatures have been previously described via NanoString profiling of solid biopsy tissue and plasma. This study validated these signatures via next-generation sequencing technology and compared their performance against clinical metrics and other published melanoma signatures., Methods: RNA from 64 plasma and 60 FFPE biopsy samples from individuals with invasive melanoma or related benign/control phenotypes was extracted and enriched for microRNA. RNA sequencing was performed to compute MEL38/MEL12 signature scores. The results were evaluated with published NanoString and RNA sequencing datasets, comprising 548 solid tissue samples and 217 plasma samples, to predict disease status and patient outcome., Results: The MEL38 diagnostic signature classifies patients into discrete diagnostic groups via RNA sequencing in either solid tissue or plasma (P < 0.001). In solid tissue, the prognostic MEL12 signature stratifies patients into low-, intermediate- and high-risk groups, independent of clinical covariates. The hazard ratios for 10-year overall survival, based on observed survival intervals, were 2.2 (MEL12 high-risk vs low-risk, P < 0.001) and 1.8 (intermediate-risk vs low-risk, P < 0.001), outperforming other published prognostic models. MEL12 also exhibited prognostic significance in the plasma of 42 patients with invasive disease., Conclusions: The MEL38 and MEL12 signatures can be assessed in either solid tissue or plasma using RNA-seq and are strong predictors of disease state and patient outcome. Compared with other genomic methods, MEL12 was shown to be the strongest predictor of poor prognosis. MicroRNA expression profiling offers objective, accurate genomic information about a patient's likelihood of invasive melanoma and prognosis., (© 2024. The Author(s).)

Background: Pituitary tumor-transforming gene 1 (PTTG1) is an important gene in tumour development. However, the relevance of PTTG1 in tumour prognosis, immunotherapy response, and medication sensitivity in human pan-cancer has to be determined., Methods: TIMER, GEPIA, the human protein atlas, GEPIA, TISCH2, and cBioportal examined the gene expression, protein expression, prognostic value, and genetic modification landscape of PTTG1 in 33 malignancies based on the TCGA cohort. The association between PTTG1 and tumour immunity, tumour microenvironment, immunotherapy response, and anticancer drug sensitivity was investigated using GSCA, TIDE, and CellMiner CDB. Molecular docking was used to validate the possible chemotherapeutic medicines for PTTG1. Additionally, siRNA-mediated knockdown was employed to confirm the probable role of PTTG1 in paclitaxel-resistant cells., Results: PTTG1 is overexpressed and associated with poor survival in most tumors. Functional enrichment study revealed that PTTG1 is involved in the cell cycle and DNA replication. A substantial connection between PTTG1 expression and immune cell infiltration points to PTTG1's possible role in the tumour microenvironment. High PTTG1 expression is associated with tumour immunotherapy resistance. The process could be connected to PTTG1, which mediates T cell exhaustion and promotes cytotoxic T lymphocyte malfunction. Furthermore, PTTG1 was found to be substantially linked with sensitivity to several anticancer medications. Suppressing PTTG1 with siRNA reduced clone formation and migration, implying that PTTG1 may play a role in paclitaxel resistance., Conclusion: PTTG1 shows potential as a cancer diagnostic, prognostic, and chemosensitivity marker. Increased PTTG1 expression is linked to resistance to cancer treatment. The mechanism could be linked to PTTG1's role in promoting cytotoxic T lymphocyte dysfunction and mediating T cell exhaustion. It is feasible to consider PTTG1, which is expressed on Treg and Tprolif cells, as a new therapeutic target for overcoming immunotherapy resistance., (© 2024. The Author(s).)

The role of circadian rhythm genes (CRGs) in gastric cancer (GC) is poorly understood. This study aimed to develop a CRG signature to improve understanding of prognosis and immunotherapy responses in GC patients. We integrated the The Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) dataset with CRGs to develop a prognostic signature for GC. The signature's predictive ability was validated using Kaplan-Meier and ROC curves. The CIBERSORT algorithm evaluated immune cell proportions, and tumor immune dysfunction and exclusion score, as well as immune phenotype score, determined the response to immunotherapy for STAD patients. Finally, we assessed signature genes expression using real-time quantitative polymerase chain reaction. We developed a 4-CRG signature for STAD, demonstrating accurate prognostic ability. The low-risk group showed increased B cell memory and CD8 + T cells, and decreased M2 Macrophages compared to the high-risk group. Patients in the low-risk group had a higher likelihood of benefiting from immunotherapy. Additionally, gastric cancer tissues exhibited elevated expression of OPN3 and decreased expression of TP53 compared to adjacent tissue. This study successfully established a prognostic signature for CRGs, accurately predicting prognosis and immunotherapeutic response among STAD patients, providing insights for the development of personalized therapeutic strategies for these patients., (© 2024. The Author(s).)

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous tumor. Commonly used tumor staging don't sufficiently and accurately assess the prognosis of HNSCC patients, resulting in a lack of guidance for clinical treatment decisions. M2 macrophage infiltration has been shown to be strongly associated with the tumor prognosis. In this study, we used the Cancer Genome Atlas (TCGA) data to screen for genes co-expressed with M2 macrophages in HNSCC. We used univariate Cox regression to screen out the genes associated with HNSCC prognosis, and constructed a HNSCC prognosis model by Lasso regression analysis. The results confirmed that the model had good predictive value and accuracy for the prognosis of HNSCC patients by survival analysis, ROC curve and nomogram. We divided the HNSCC samples into high-risk and low-risk groups according to the risk score, and the results showed that patients in the high-risk group were more prone to genetic mutations and had a higher tumor mutational burden. In addition, there were significant differences between risk groups in terms of immune cell infiltration and drug sensitivity. The HNSCC prognostic model established in this study may provide guidance for clinical therapeutic decision-making and provide a theoretical foundation for the development of new immunotherapy methods., (© 2024. The Author(s).)

Accumulating research showed that ENC1 plays a critical role in maintaining the physiological functions. However, little is known about its role in predicting prognosis and immunotherapy response across cancers. In our results, compared to normal tissues, most cancer tissues exhibit increased ENC1 expression. We found that the most common type of genetic variation was gene mutation. In addition, a positive correlation was found between CNV and ENC1 expression. Moreover, the overexpression of ENC1 was positively correlated with poor clinical outcomes. The GSEA results showed that ENC1 is closely correlated with tumor-promoting biological functions in most cancers. ENC1 is also closely negatively associated with the infiltration levels of T cells, activated NK cells, and B cells. Most immunomodulators are positively associated with ENC1. Further, we verified that inhibition of ENC1 expression suppressed the proliferation and migration of breast cancer, pancreatic cancer and glioma cells. In conclusion, our study demonstrated that ENC1 plays a protumorigenic role in most cancers. Additionally, ENC1 is closely correlated with tumor microenvironment features and immune checkpoint inhibitors expression. Overall, ENC1 could serve as a promising potential prognostic biomarker in various tumors., (© 2024. The Author(s).)

Background: Cholangiocarcinoma is a highly heterogeneous tumor with bile acid metabolism involving in its development. The aim of this study was to characterize bile acid metabolism and identify specific subtypes to better stratify cholangiocarcinoma patients for individualized treatment and prognostic assessment., Methods: A total of 30 bile acids were quantified using the ultra-performance liquid chromatography tandem mass spectrometry. Using Consensus clustering, the molecular subtypes related to bile acid metabolism were identified. The prognosis, clinicopathologic characteristics, immune landscape, and therapeutic response were compared between these subtypes. The single-cell RNA sequencing (scRNA-seq) analysis and preliminary cell experiment were also conducted to verify our findings., Results: The altered bile acid profile and genetic variation of bile acid metabolism-related genes in cholangiocarcinoma were demonstrated. The cholangiocarcinoma was categorized into bile acid metabolism-active and -inactive subtypes with different prognoses, clinicopathologic characteristics, tumor microenvironments (TME) and therapeutic responses. This categorization was reproducible and predictable. Specifically, the bile acid metabolism-active subtype showed a poor prognosis with an immunosuppressive microenvironment and an inactive response to immunotherapy, while the bile acid metabolism-inactive subtype showed the opposite characteristics. Moreover, the scRNA-seq revealed that immunotherapy altered bile acid metabolism in TME of cholangiocarcinoma. Finally, a prognostic signature related to bile acid metabolism was developed, which exhibited strong power for prognostic assessment of cholangiocarcinoma. Consistently, these results were verified by immunohistochemistry, cell proliferation, migration, and apoptosis assays., Conclusion: In conclusion, a novel cholangiocarcinoma classification based on bile acid metabolism was established. This classification was significant for the estimation of TME and prognosis., (© 2024. The Author(s).)

Background: Ovarian cancer (OC) is one of the cancers with a high incidence at present, which poses a severe threat to women's health. This study focused on identifying the heterogeneity among malignant epithelial cell OC and constructing an effective prognostic signature to predict prognosis and immunotherapy according to a multidisciplinary study., Methods: The InterCNV algorithm was used to identify the heterogeneity of OC based on the scRNA-seq and bulk RNA-seq data. Six algorithms selected EMTscore. An effective prognostic signature was conducted using the COX and Least Absolute Shrinkage and Selection Operator (LASSO) regression algorithms. The texting datasets were used to assess the accuracy of the prognostic signature. We evaluated different immune characteristics and immunotherapy response differences among other risk groups., Results: A prognostic signature including 14 genes was established. The patients in the high-risk group have poor survival outcomes. We also found that the patients in the low-risk group have higher immune cell infiltration, enrichment of immune checkpoints, and immunotherapy response, suggesting that the patients in the low-risk group may be more sensitive to immunotherapy. Finally, the laboratory test results showed that KREMEN2 was identified as a novel biomarker and therapeutic target for OC patients., Conclusions: Our study established a GRG signature consisting of 16 genes based on the scRNA-seq and bulk RNA-seq data, which provides a new perspective on the prediction of prognosis and treatment strategy for OC., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Altered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD) immunotherapy and prognosis was not entirely clear., Methods: We analyzed SLC4A4 expression in LUAD tissues and cell lines using quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. The effects of SLC4A4 overexpression on angiogenesis, cell migration, invasion, and epithelial-mesenchymal transition were examined. Public databases helped construct a risk model evaluating SLC4A4's expression on LUAD prognosis and immunotherapy response. Additionally, a xenograft model, flow cytometry, and enzyme-linked immunosorbent assay further explored SLC4A4's role in tumor immune microenvironment infiltration., Results: Upregulation of SLC4A4 promoted apoptosis in the LUAD cell line and significantly inhibited the migration and invasive ability of cancer cells (P<0.01). A total of 10 key genes (including SIGLEC6, RHOV, PIR, MOB3B, MIR3135B, LPAR6, KRT8, ITGA2, CPS1, and C6) were screened according to SLC4A4 expression, immune score and stromal score, and a prognostic model with good outcome was constructed (AUC values of which in the training cohort at 1,3, and 5 years reached 0.73, 0.73, and 0.72, respectively). Importantly, we demonstrated that high expression of SLC4A4 was able to increase the proliferation level and cytokine secretion of CD8+ T cells for the purpose of promoting the immune system response to LUAD., Conclusion: Our study revealed that SLC4A4 can serve as a prognostic indicator for LUAD, providing new insights into the treatment and diagnosis of LUAD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: The incidence of clear cell renal cell carcinoma (ccRCC) is increasing annually. While the cure rate and prognosis of early ccRCC are promising, the 5-year survival rate of patients with metastatic ccRCC is below 12%. Autophagy disfunction is closely related to infection, cancer, neurodegeneration and aging. Nevertheless, there has been limited exploration of the association between autophagy and ccRCC through bioinformatics analysis., Methods: A novel risk model of autophagy-related genes (ARGs) was constructed to predict the prognosis of patients with ccRCC and guide the individualized treatment to some extent. Relevant data samples were obtained from the TCGA database, and ccRCC-related ARGs were identified by Pearson correlation analysis, leading to the establishment of a risk model covering 10 ccRCC-related ARGs. Many indicators were used to assess the accuracy of the risk model., Results: Receiver operating characteristic (ROC) curve analysis showed that the risk model had high accuracy, indicating that the risk model could predict the prognosis of ccRCC patients. Moreover, the findings revealed significant differences about immune and metabolic features in low- and high-risk groups. The study also found that BAG1 within the risk model was closely related to the prognosis of ccRCC and an independent risk factor. In vitro and in vivo experiments validated for the first time that BAG1 could suppress the proliferation, migration, and invasion of ccRCC., Conclusion: The construction of ARGs risk model, can well predict the prognosis of ccRCC patients, and provide guidance for individual therapy to patients. It was also found that BAG1 has significant prognostic value for ccRCC patients and acts as a tumor suppressor gene in ccRCC. These findings have crucial implications for the prognosis and treatment of ccRCC patients., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: The aim of this study was to assess the prognostic significance of α-1,3-mannitrotransferase (ALG3) in triple-negative breast cancer (TNBC) and investigate its impact and potential mechanism on the efficacy of anti-PD-1 therapy., Methods: Bioinformatics analysis was used to examine the expression of ALG3 in cancer patients using UACLAN and other databases. The associations of the ALG3 gene and the clinicopathological features of breast cancer were examined with bc-GenExMiner database. Correlation between ALG3 expression and survival was further established utilizing the Kaplan-Meier Plotter database. Immunohistochemistry (IHC) was used to analyze the expression of ALG3 in cohort of breast cancer patients from Hubei cancer hospital to confirmed the prognostic value of ALG3 in TNBC. The effect of ALG3 on the levels of infiltrating immune cells was also analyzed. And the mutation module within cBioPortal was utilized to visualize ALG3 mutations in BRCA. The CRISPR/Cas9 technique was used to establish ALG3 low-expression TNBC cell lines. Influence of ALG3 expression on cancer cell proliferation and chemotherapeutic responsiveness was scrutinized in vitro. Animal models were constructed to evaluate the alteration of tumor sensitivity to anti-PD-1 therapy with decreased ALG3 expression. And flow cytometry and IHC were used to investigate the tumor immune microenvironment. Association of PD-L1 Glycosylation and ALG3 expression were also investigated by western blot., Results: ALG3 expression was elevated in TNBC and was strikingly linked to unfavorable clinical features such as lymphatic node metastasis, high NPI, advanced stage and age, etc. Furthermore, high ALG3 expression was associated with shorter OS in TNBC patients. Mechanistically, ALG3 expression was negatively correlated with the infiltration of CD8 + T cells, CD4 + T cells, and NK cells. ALG3-KO cells had increased sensitivity to chemotherapeutic agents. In animal models, the volume of ALG3-KO tumors was lower than the control group with immunotherapy. ALG3-KO tumors showed an increased proportion of CD8 + T cells, while a decreased proportion of regulatory T cells and M2-type macrophages. The expression level of PD-L1 protein was not affected by ALG3 level, but the glycosylation level was significantly decreased in tumor. Similarly, the glycosylation level of PD-L1 is reduced in ALG3-KO cell in vitro. Additionally, ALG3 knockout lead to reduced tolerance of tumor cells to IFN-γ, thereby enhancing the efficacy of immunotherapy., Conclusion: ALG3 is a potential biomarker for poor prognosis of TNBC and may reduce the efficacy of immunotherapy by modulating the tumor microenvironment and glycosylation of PD-L1., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Epithelial ovarian carcinoma (EOC) is the most fatal among female reproductive system tumors. The immune tumor microenvironment and ubiquitin-proteasome pathway are closely related to the proliferation, invasion, and response to chemotherapy in EOC. However, their specific roles in EOC have not been fully elucidated. Therefore, we aimed to recognize potential prognostic markers and novel therapeutic targets for EOC. We constructed the ubiquitin-related signature risk model comprising HSP90AB1, FBXO9, SIGMAR1, STAT1, SH3KBP1, EPB41L2, DNAJB6, VPS18, PPM1G, AKAP12, FRK, and PYGB, specifically for patients with EOC. The high-risk model presented a worse prognosis, primarily associated with the B-cell receptor signaling pathway, ECM receptor interaction, focal adhesion, and actin cytoskeleton regulations. Analysis of the immune landscape revealed a higher abundance of B cells, M2 macrophages, neutrophil CD4 T cells, cancer-associated fibroblasts, macrophage neutrophils, and fibroblasts in the high-risk group. It also exhibited lower tumor mutation burden, mRNAsi, and EREG-mRNAsi and reduced sensitivity to other chemotherapy drugs, except dasatinib. These findings serve as a valuable indicator for personalized treatment strategies and clinical stratification in managing patients with EOC. Additionally, our study will serve as a foundation for future mechanistic research to explore the association between the ubiquitin-proteasome pathway and EOC., (© 2024. The Author(s).)

Background: The HER-2 status of breast cancer (BC) has been classified as negative or positive for a long time. Given the efficacy of novel anti-HER2-targeted antibody drug conjugates (ADCs) in HER2-low BC, a distinct subgroup of HER2-low tumors has emerged within BC. The biology and prognostic impact of HER2-low expression are not yet well defined, and inconsistent results were reported. This study aims to evaluate the impact of low HER-2 status on the response to neoadjuvant chemotherapy (NACT) and disease- free survival (DFS) rates., Methods: We retrospectively analyzed BC patients treated with NACT from 2017 to 2023 in two cancer centers. HER2-negative patients were included. HER-2 low status was defined by IHC + 1 or + 2/ISH non-amplified, and HER2-zero was defined by IHC 0. Pathological complete response (pCR) rates and DFS between HER2-low and HER2-zero populations were compared., Results: 170 patients were identified. 122 (72%) of these patients were HER2- zero BC, whereas 48 (28%) were HER2-low BC. Overall, pCR was achieved in 35 (20.5%) patients. Of these, pCR was observed in 30 patients (44.6%) from the HER2- zero group, compared to 5 patients (10.4%) from the HER2-low group (p = 0.046), but significance was lost in multivariate analysis. Among the hormone receptor (HR) positive subtype, pCR was achieved 19.8% of HER2-zero tumors and 7.5% of HER2-low tumors (p = 0.08). For HR-negative subtype 34.1% HER2-zero tumors had pCR and 25% of the HER2-low tumors had pCR (p = 0.614). There was no association between DFS and HER2-low status., Conclusions: Our study indicates that HER2-low status had no impact on pCR or DFS., (© 2024. The Author(s).)

Epidemiological surveys have shown that the incidence of type 2 diabetes mellitus (T2DM) and malignancies is rapidly increasing worldwide and has become a major disease that threatens human life. In this study, we quantitatively analyzed the proteome of tumor tissues and adjacent normal tissues from six patients withT2DM combined with colorectal cancer (CRC) and eight non-diabetic CRC, focusing on the effect of T2DM on tumor tissues. We analyzed the functional enrichment of differentially expressed proteins (DEPs) using clusterProfiler in R and the expression level of protein tyrosine phosphatase non-receptor type 11 (PTPN11) and other key proteins in the TIMER and GEPIA2 databases. The HPA database was used to validate PTPN11 protein expression. The correlation between PTPN11 expression and clinicopathological features was analyzed by UALCAN database. The impact of PTPN11 on clinical prognosis was evaluated utilizing Kaplan-Meier Plotter. The correlation between PTPN11 expression and tumor-infiltrated immune cells was investigated via TIMER and TISIDB databases. Gene set enrichment analysis (GSEA) was performed to examined the pathway of PTPN11 enrichment in CRC using data from The Cancer Genome Atlas (TCGA) database. Furthermore, small interfering (si) RNA was used to knock down PTPN11 in CRC cell line SW480. Western blot analysis was used to detect PTPN11 expression in tissue samples or cells and the effect of PTPN11 knockdown on key proteins related to PI3K/AKT and cell cycle pathway in SW480 cells. Cell proliferation and wound healing assays were used to detect the effects of cell proliferation and migration after knockdown of PTPN11 or treatment with high glucose. We found that metabolic pathways such as oxidative phosphorylation, glycolysis/gluconeogenesis, and insulin secretion were significantly enriched in tumor tissues from diabetic patients compared to non-diabetic patients. In addition, PTPN11, a marker gene associated with T2DM and CRC, were mined in diabetic tumor tissues. PTPN11 showed high expression in diabetic tumor tissues compared to normal tissues. High PTPN11 expression predicted poor prognosis in CRC. PTPN11 expression was strongly associated with immune infiltrating cells in CRC. GSEA analysis revealed that PTPN11 was enriched in cancer-related pathways. Western blotting analysis indicated that PTPN11 knockdown reduced the protein levels of p-PI3K, p-AKT, CDK1 and CYCLIN D, without altering PI3K and AKT protein levels. Cell proliferation and wound healing data showed that PTPN11 and high glucose could increase the proliferation and migration ability. These findings showed that PTPN11 may be a potential key biomarker for CRC in patients with diabetes, which will provide new potential targets for future intervention of T2DM complicated with CRC., (© 2024. The Author(s).)

Copper-induced cell death is regulated through protein lipoylation, which is critical for gene expression and phenotypic regulation. Neverless, the role of Cuproptosis-related genes in breast cancer (BC) remains unknown. This study aimed to construct a prognostic signature based on the expression of Cuproptosis-related genes in order to guide the diagnosis and treatment for BC. Cuproptosis-related genes prognostic signature has ata of 1250 BC tissues and 583 normal breast tissues were obtained from The Cancer Genome Atlas (TCGA), Genotype Tissue Expression (GTEx), and GEO GSE65212. The prognostic signature was established and evaluated with nineteen Cuproptosis-related genes. A series of in silico analyses based on SLC31A1, included expression analysis, independent prognostic analysis, correlation analysis, immune-related analysis and survival analysis. Finally, a series of cell experiments (including quantitative real-time polymerase chain reaction and western blot), and mice experiments were applied to evaluate the impact of SLC31A1 on BC. Cuproptosis-related genes prognostic signature has good predictive promising for survival in BC patients. We discovered that SLC31A1SLC31A1 was overexpressed in BC and was its independent prognostic factor. High expression of the SLC31A1 was correlated with poor prognosis and immune infiltrating of BC. SLC31A1 expression is associated with immune, chemotherapeutic and targeted therapy outcomes in BC. The proliferation, migration, and invasiveness of Her2 + enriched BC cells were decreased by SLC31A1 knockdown, also resulting in a decrease in tumor volume in mouse model. SLC31A1 is a candidate biomarker or therapeutic target in precision oncology, with diagnostic and prognostic significance in BC., (© 2024. The Author(s).)

PI3K/AKT/mTOR pathway is implicated in breast cancer progression and recurrence. The identification of PIK3CA and AKT1 mutations and loss of PTEN serve as selection criterion for targeted therapies involving selective inhibitors. However, they do not consistently align with pathway activation, and high-cost determinations limit their routine application. PI3K-downstream epigenetic regulatory mechanisms broaden the alterations that amplify pathway activity and, consequently, sensitivity to selective inhibitors. In this retrospective observational study, conducted within a cohort of early-stage breast cancer patients, we determined phosphorylated ribosomal protein S6 (pS6) at Ser240/244 by immunohistochemistry as an indicator of PI3K pathway activation. Log-Rank test and Cox proportional hazards regression were used to analyze the clinical relevance of pS6, alone and together with clinicopathological variables, regarding recurrence-free survival. ROC curves and the area under the curves were used to evaluate the calibration and discrimination properties of uni- and multivariate models. Our results show that a high percentage of pS6 positive tumor cells was associated with an unfavorable prognosis in a cohort of 129 hormone receptor positive/HER2 negative breast cancer patients (Hazard Ratio = 5.92; Log-Rank p = 9.5e-08; median follow-up = 53 months). When assessed in combination with lymph node status, the predictive capacity was higher compared to both univariate models individually. In conclusion, pS6 could represent a novel independent marker for predicting recurrence risk in luminal breast cancer., (© 2024. The Author(s).)

Background: Pancreatic ductal adenocarcinoma (PDAC) poses a significant challenge due to late-stage diagnoses resulting from nonspecific early symptoms and the absence of early diagnostic biomarkers. MicroRNAs (miRNAs) play a crucial role in regulating diverse biological processes, and their abnormal expression is observed in various diseases, including cancer. Cancer stem cells (CSCs) are thought to act as a driving force in PDAC spread and recurrence. In pursuing the goal of unravelling the complexities of PDAC and its underlying molecular mechanisms, our study aimed to identify PDAC-associated miRNAs and relate them to disease progression, focusing on their involvement in various PDAC stages in patients and in reliable in vitro models, including pancreatic CSC (PaCSC) models., Methods: The miRNA profiling datasets of serum and solid biopsies of PDAC patients deposited in GEO DataSets were analyzed by REML-based meta-analysis. The panel was then investigated by Real Time PCR in serum and solid biopsies of 37 PDAC patients enrolled in the study, as well as on BxPC-3 and AsPC-1 PDAC cell lines. We extended our focus towards a possible role of PDAC-associated miRNAs in the CSC phenotype, by inducing CSC-enriched pancreatospheres from BxPC-3 and AsPC-1 PDAC cell lines and performed differential miRNA expression analysis between PaCSCs and monolayer-grown PDAC cell lines., Results: Meta-analysis showed differentially expressed miRNAs in blood samples and cancerous tissues of PDAC patients, allowing the identification of a panel of 9 PDAC-associated miRNAs. The results emerging from our patients fully confirmed the meta-analysis for the majority of miRNAs under investigation. In vitro tasks confirmed the aberrant expression of the panel of PDAC-associated miRNAs, with a dramatic dysregulation in PaCSC models. Notably, PaCSCs have shown significant overexpression of miR-4486, miR-216a-5p, and miR-216b-5p compared to PDAC cell lines, suggesting the recruitment of such miRNAs in stemness-related molecular mechanisms. Globally, our results showed a dual behaviour of miR-216a-5p and miR-216b-5p in PDAC while miR-4486, miR-361-3p, miR-125a-5p, miR-320d expression changes during the disease suggest they could promote PDAC initiation and progression., Conclusions: This study contributed to an enhanced comprehension of the role of miRNAs in the development and progression of PDAC, shedding new light on the miRNA landscape in PDAC and its intricate interplay with CSCs, and providing specific insights useful in the development of miRNA-based diagnostic biomarkers and therapeutic targets., (© 2024. The Author(s).)

Extensive research has demonstrated that dysregulation of costimulatory molecule expression plays a pivotal role in cancer biology. However, the impact of intratumoral CD70 on the initiation, progression, and immune response in diffuse large B-cell lymphoma (DLBCL) remains poorly understood. This study aims to elucidate the clinical significance of CD70 in DLBCL diagnosis and prognosis, as well as its relationship with the immune microenvironment. We first analyzed CD70 expression across various cancers, including DLBCL, using multiple online databases (TIMER, GEPIA, GENT2, TNMPlot, GSCA, and GEO). We then evaluated the clinical correlations and prognostic value of CD70 in DLBCL. Additionally, we investigated the functional role of CD70 in DLBCL cells. Genomic alterations of CD70 were analyzed using the cBioPortal online tool. Co-expression network analysis was performed to assess the biological functions associated with CD70. Furthermore, we utilized TIMER2.0 to examine the correlation between CD70 expression and immune cell infiltration. Our results revealed that CD70 expression was significantly upregulated in DLBCL tissues compared to matched normal tissues, and high CD70 expression was associated with poor clinical outcomes in DLBCL patients. In vitro experiments demonstrated that CD70 inhibition promotes apoptosis and induces G1 phase arrest in DLBCL cells. Genomic alteration analysis showed that patients with CD70 alterations exhibited worse overall survival compared to those without such alterations. Co-expression and functional enrichment analyses indicated that CD70 is functionally related to tumor necrosis factor receptor binding and the NF-κB signaling pathway. Moreover, we found that CD70 expression levels were negatively correlated with B cell and NK cell infiltration in DLBCL. In conclusion, this study suggests that CD70 is a potential diagnostic and therapeutic biomarker for DLBCL. Our findings provide valuable insights for the development of novel therapeutic strategies targeting CD70 in DLBCL treatment., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The most common type of non-small cell lung cancer is lung adenocarcinoma (LUAD), which is characterized by high morbidity and poor survival. Up-regulation of SASS6 expression can lead to the progression of various malignant tumors. However, there are no relevant studies on the role of SASS6 in LUAD. SASS6 was highly expressed in most tumors, reflecting a good diagnostic value, and its overexpression in LUAD indicated discouraging overall prognosis. Functional enrichment analysis suggested that SASS6 was associated with cell cycle in LUAD. In addition, patients with high SASS6 expression had worse immune infiltration, but higher TMB and immune checkpoint, and higher sensitivity to multiple targeted drugs such as osimertinib. Cell experiments confirmed that knockdown of SASS6 could inhibit the viability of tumor cells.SASS6 has important value in the diagnosis of cancer. In particular, SASS6 is a crucial factor in the progression of LUAD, and has important clinical value, especially in the diagnosis, prognosis and treatment., (© 2024. The Author(s).)

MicroRNAs are involved in breast cancer development and progression, holding potential as biomarkers and therapeutic targets or tools. The roles of miR-20a-5p, a member of the oncogenic miR-17-92 cluster, remain poorly understood in the context of breast cancer. In this study, we elucidate the role of miR-20a-5p in breast cancer by examining its associations with breast cancer risk factors and clinicopathological features, and its functional roles in vitro. Tissue microarrays from 313 CAMO cohort breast cancer surgical specimens were constructed, in situ hybridization was performed and miR-20a-5p expression was semiquantitatively scored in tumor stromal fibroblasts, and in the cytoplasm and nuclei of cancer cells. In vitro analysis of the effect of miR-20a-5p transfection on proliferation, migration and invasion was performed in three breast cancer cell lines. High stromal miR-20a-5p was associated with higher Ki67 expression, and higher odds of relapse, compared to low expression. Compared to postmenopausal women, women who were premenopausal at diagnosis had higher odds of high stromal and cytoplasmic miR-20a-5p expression. Cytoplasmic miR-20a-5p was significantly associated with tumor grade. In tumors with high cytoplasmic miR-20a-5p expression compared to low expression, there was a tendency towards having a basal-like subtype and high Ki67. In contrast, high nuclear miR-20a-5p in cancer cells was associated with smaller tumor size and lower odds of lymph node metastasis, compared to low nuclear expression. Transfection with miR-20a-5p in breast cancer cell lines led to increased migration and invasion in vitro. While the majority of our results point towards an oncogenic role, some of our findings indicate that the associations of miR-20a-5p with breast cancer related risk factors and outcomes may vary based on tissue- and subcellular location. Larger studies are needed to validate our findings and further investigate the clinical utility of miR-20a-5p., (© 2024. The Author(s).)

Background: Breast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis., Methods: We used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level., Results: Our single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets., Conclusions: This study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management., (© 2024. The Author(s).)

Background: Breast cancer is a significant public health issue worldwide, being the most prevalent cancer among women and a leading cause of death related to this disease. The molecular processes that propel breast cancer progression are not fully elucidated, highlighting the intricate nature of the underlying biology and its crucial impact on global health. The objective of this research was to perform bioinformatics analyses on breast cancer-related datasets to gain a comprehensive understanding of the molecular mechanisms at play and to identify key genes associated with the disease., Methods: The toolkit analyses involve techniques such as differential gene expression analysis, Gene Set Enrichment Analysis (GSEA), Weighted Co-Expression Network Analysis (WGCNA), and Machine Learning algorithms. Furthermore, in vitro cell experiments have demonstrated the impact of HSPB6 on cell migration, proliferation, and apoptosis., Results: The study identified multiple genes that displayed differential expression in breast cancer, notably FHL1 and HSPB6. A machine learning model was developed in this study and specifically trained for breast cancer diagnosis using these genes, achieving high precision. Furthermore, analysis of immune cell infiltration revealed an enrichment of Tregs and M2 macrophages in the treated group, showcasing its significant impact on the tumor's immunological context. A temporal analysis of breast cancer cells using single-cell RNA sequencing provided insights into cellular developmental trajectories and highlighted changes in expression patterns across key genes during disease progression. The upregulation of HSPB6 in MCF7 cells significantly inhibited both cell migration and proliferation abilities, suggesting that promoting HSPB6 expression could induce ferroptosis in breast cancer cells., Conclusion: Our findings have identified compelling molecular targets and distinctive diagnostic markers for the clinical management of breast cancer. This data will serve as crucial guidance for further research in the field., (© 2024. The Author(s).)

The identification of predictors for immunotherapy is often hampered by the absence of control groups in many studies, making it difficult to distinguish between prognostic and predictive biomarkers. This study presents biomarker analyses from the phase 3 CONTINUUM trial (NCT03700476), the first to show that adding anti-PD-1 (aPD1) to chemoradiotherapy (CRT) improves event-free survival (EFS) in patients with locoregionally advanced nasopharyngeal carcinoma. A dynamic single-cell atlas was profiled using mass cytometry on peripheral blood mononuclear cell samples from 12 pairs of matched relapsing and non-relapsing patients in the aPD1-CRT arm. Using a supervised representation learning algorithm, we identified a Ki67 + proliferating regulatory T cells (Tregs) population expressing high levels of activated and immunosuppressive molecules including FOXP3, CD38, HLA-DR, CD39, and PD-1, whose abundance correlated with treatment outcome. The frequency of these Ki67 + Tregs was significantly higher at baseline and increased during treatment in patients who relapsed compared to non-relapsers. Further validation through flow cytometry (n = 120) confirmed the predictive value of this Treg subset. Multiplex immunohistochemistry (n = 249) demonstrated that Ki67 + Tregs in tumors could predict immunotherapy benefit, with aPD1 improving EFS only in patients with low baseline levels of Ki67 + Tregs. These findings were further validated in the multicenter phase 3 DIPPER trial (n = 262, NCT03427827) and the phase 3 OAK trial of anti-PD-L1 immunotherapy in NSCLC, underscoring the predictive value of Ki67 + Treg frequency in identifying the beneficiaries of immunotherapy and potentially guiding personalized treatment strategies., (© 2024. The Author(s).)

Background: Cancer is the leading cause of disease-related mortality in children. Causes of leukemia, the most common form, are largely unknown. Growing evidence points to an origin in-utero, when global redistribution of DNA methylation occurs driving tissue differentiation., Methods: Epigenome-wide DNA methylation was profiled in surrogate (blood) and target (bone marrow) tissues at birth, diagnosis, remission and relapse of pediatric pre-B acute lymphoblastic leukemia (pre-B ALL) patients. Double-blinded analyses was performed between prospective cohorts extending from birth to diagnosis and retrospective studies backtracking from clinical disease to birth. Validation was carried out using independent technologies and populations., Results: The imprinted and immuno-modulating VTRNA2-1 was hypermethylated (FDR<0.05) at birth in nested cases relative to controls in all tested populations (totaling 317 cases and 483 controls), including European and Hispanic ancestries. VTRNA2-1 methylation was stable over follow-up years after birth and across surrogate, target and other tissues (n=5,023 tissues; 30 types). When profiled in leukemic tissues from two clinical cohorts (totaling 644 cases), VTRNA2-1 methylation exhibited higher levels at diagnosis relative to controls, it reset back to normal levels at remission, and then re-increased to above control levels at relapse. Hypermethylation was significantly associated with worse pre-B ALL patient survival and with reduced VTRNA2-1 expression (n=2,294 tissues; 26 types), supporting a functional and translational role for VTRNA2-1 methylation., Conclusion: This study provides proof-of-concept to detect at birth epigenetic precursors of pediatric pre-B ALL. These alterations were reproducible with different technologies, in three continents and in two ethnicities, and can offer biomarkers for early detection and prognosis as well as actionable targets for therapy., (© 2024. The Author(s).)

Glioblastomas (GBMs) are the most aggressive types of central nervous system tumors. Although certain genomic alterations have been identified as prognostic biomarkers of GBMs, the histomorphological features that predict their prognosis remain elusive. In this study, following an integrative diagnosis of 227 GBMs based on the 2021 World Health Organization classification system, the cases were histologically fractionated by cellular variations and abundance to evaluate the relationship between cellular heterogeneity and prognosis in combination with O-6-methylguanine-DNA methyltransferase gene promoter methylation (mMGMTp) status. GBMs comprised four major cell types: astrocytic, pleomorphic, gemistocytic, and rhabdoid cells. t-distributed stochastic neighbor embedding analysis using the histological abundance of heterogeneous cell types identified two distinct groups with significantly different prognoses. In individual cell component analysis, the abundance of gemistocytes showed a significantly favorable prognosis but confounding to mMGMTp status. Conversely, the abundance of epithelioid cells was correlated with the unfavorable prognosis. Linear model analysis showed the favorable prognostic utility of quantifying gemistocytic and epithelioid cells, independent of mMGMTp. The evaluation of GBM cell histomorphological heterogeneity is more effective for prognosis prediction in combination with mMGMTp analysis, indicating that histomorphological analysis is a practical and useful prognostication tool in an integrative diagnosis of GBMs., (© 2024. The Author(s).)

Pyroptosis plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the pyroptosis-related gene (PRG) expression pattern and to identify promising pyroptosis-related biomarkers to improve the prognosis of LUAD. The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the 44 differentially expressed PRGs (DEPRGs). Then, consensus clustering revealed pyroptosis-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic PRGs. After overlapping DEGs and the Lasso regression analysis-based prognostic genes, the predictive risk model was established and validated. Correlation analysis between PRGs and clinicopathological variables was also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels, the risk score, and clinicopathological variables in the predictive risk model. A total of 52 genes from the PubMed were identified as PRGs, and 44 of the 52 genes were pooled as DEPRGs. The most significant GO term was "collagen trimer" (P = 2.46E-13), and KEGG analysis results indicated that 44 DEPRGs were significantly enriched in Salmonella infection (P < 0.001). Then, consensus clustering analysis divided LUAD patients into two clusters, and a total of 79 DEGs were identified according to these cluster subtypes. Subsequently, univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators and we also performed Lasso regression analysis and screened 23 DEGs. After overlapping 23 DEGs and 12 genes, only 4 (KLRG2, MAPK4, C6 and SFRP5) of 12 genes were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model effectively predicted the prognosis (P < 0.001). Combined with the correlation analysis results between the 4 genes and clinicopathological variables, C6 and KLRG2 were screened as prognostic genes. In this study, we constructed a predictive risk model and identified two pyroptosis subtype-related gene expression patterns to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful for accurately characterizing the LUAD and developing personalized treatment., (© 2024. The Author(s).)

Circulating cell-free DNA (cfDNA) assays for monitoring individuals with cancer typically rely on prior identification of tumor-specific mutations. Here, we develop a tumor-independent and mutation-independent approach (DELFI-tumor fraction, DELFI-TF) using low-coverage whole genome sequencing to determine the cfDNA tumor fraction and validate the method in two independent cohorts of patients with colorectal or lung cancer. DELFI-TF scores strongly correlate with circulating tumor DNA levels (ctDNA) (r = 0.90, p < 0.0001, Pearson correlation) even in cases where mutations are undetectable. DELFI-TF scores prior to therapy initiation are associated with clinical response and are independent predictors of overall survival (HR = 9.84, 95% CI = 1.72-56.10, p < 0.0001). Patients with lower DELFI-TF scores during treatment have longer overall survival (62.8 vs 29.1 months, HR = 3.12, 95% CI 1.62-6.00, p < 0.001) and the approach predicts clinical outcomes more accurately than imaging. These results demonstrate the potential of using cfDNA fragmentomes to estimate tumor burden in cfDNA for treatment response monitoring and clinical outcome prediction., (© 2024. The Author(s).)

Background: Hepatocellular carcinoma (HCC) is a malignant tumor characterized by a high mortality rate. The occurrence and progression of HCC are linked to oxidative stress. Glyoxalase-1 (GLO1) plays an important role in regulating oxidative stress, yet the underlying mechanism remains unclear. GLO1 may serve as a prognostic biomarker and therapeutic target for HCC., Methods: Based on TCGA database hepatocellular carcinoma samples, we conducted a bioinformatics analysis to explore the correlation between GLO1 expression and HCC cell proliferation and viability. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that differentially expressed genes (DEGs) were mainly enriched in the cell cycle pathway. We analyzed the relationships between GLO1 and 24 genes enriched in the cell cycle pathway using a protein-protein interaction (PPI) network. Finally, experimental validation was performed to assess GLO1's impact on the distribution of cells at different cell cycle stages and on the proliferation and migration of HCC cells., Results: Our study demonstrated that GLO1 was overexpressed in HCC tissues and was associated with a poor prognosis. Data analysis indicated that overexpression of GLO1 activated the cell cycle pathway and positively correlated with expression of the majority of key cell cycle genes. Experimental validation showed that GLO1 expression affects the number of HCC cells in G2 and S phases and regulates HCC cell proliferation and migration., Conclusions: GLO1 represents a promising therapeutic target for HCC, providing valuable insights into its role in the viability and proliferation of HCC cells., (© 2024. The Author(s).)

The therapeutic approach to thymic cysts remains a subject of controversy. Predicted biomarkers for identifying thymic cysts and thymoma (THYM) are crucial. In this research, patients diagnosed with thymic cysts (MTC, n = 6) and thymoma (B1, n = 6; B3, n = 6) were enrolled. Proteins of superior quality were subjected to TMT labeling and UPLC-MS, and differentially expressed proteins (DEPs) were identified. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interactive network analyses were applied to the DEPs. Some key differentially expressed genes(DEGs) were corroborated through GEPIA 32. The pan-cancer expression levels of key DEGs remarkably linked with prognosis were determined utilizing The University of ALabama at Birmingham CANcer data analysis Portal (UALCAN). Eventually, 49 DEPs were identified in the B1 vs. MTC comparison (17 upregulated and 32 downregulated), 27 in the B3 vs. MTC comparison (8 upregulated and 19 downregulated), and 38 in the B3 vs. B1 comparison (9 upregulated and 29 downregulated). IL13RA1 (down), galectin-3 binding protein (LGALS3BP)(up), PRCSH (down), C3 (down), MXRA5 (down), TNN (down), CFHR1 (down), SUN3 (down) were jointly altered in both B1 vs. NZ and B3 vs. NZ. GEPIA validated that LGALS3BP was significantly upregulated in thymoma patients. In conclusion, LGALS3BP might be an essential biomarker to identify thymoma from the thymic cyst., (© 2024. The Author(s).)

Introduction: Faced to the growing development of collecting systematic molecular analyses in relapsed pediatric cancers to transform their targeted matched therapies, this study aimed to assess the clinical and therapeutic indications of systematic diagnostic genomic explorations performed in pediatric solid cancers to determine which type of screening and if it afford at relapse time an accurate targeted strategy., Methods: A total of 280 patients less than 22 years, referred at the University Hospitals of Strasbourg for a newly diagnosed solid tumor from January 2015 to December 2021, were prospectively genomically investigated since diagnosis. Using 7 different molecular tests going from single-gene methods (IHC, FISH, RT-PCR, Sanger sequencing, droplet digital PCR) to largescale analyses (Next-Generation sequencing, RNAsequencing and FoundationOne®CDx), we explored retrospectively the molecular findings in those pediatric solid tumors (except hematolymphoid cancers) to improve diagnosis, prognosis assessment and relapse therapeutics., Results: One hundred and ninety-eight patients (71%) underwent molecular biology (MB) at diagnosis. Thirty-eight different histologies were grouped into cerebral tumors (30%), sarcomas (26%, bone and soft tissues), various blastomas (27%), and other entities (17%). Over a median 40-month follow-up, the overall survival rate of patients was 85% and the relapse rate 28%. Of the 326 analyses carried out, 245 abnormalities (single nucleotide variations: 50%, fusions: 25%, copy number alteration: 20%) concerning 70 oncogenes were highlighted. The overall clinical impact rate was 84%. Broad-spectrum analyses had a higher therapeutic impact (57%) than the targeted analyses (28%). 75% of broad-spectrum tests found an actionable variant conducting 23% of patients to receive rapidly a matched targeted therapy since first relapse., Conclusion: Our experience highlighted the clinical utility of molecular profiling of solid tumors as soon as at diagnosis in children to expect improving access to innovative agents at relapse., (© 2024. The Author(s).)

This study aimed to identify diagnostic gene biomarkers for colorectal cancer (CRC) by analyzing differentially expressed genes (DEGs) in tumor and adjacent normal samples across five colon cancer gene-expression profiles (GSE10950, GSE25070, GSE41328, GSE74602, GSE142279) from the Gene Expression Omnibus (GEO) database. Intersecting identified DEGs with the module with the highest correlation to gene expression patterns of tumor samples in the gene co-expression network analysis revealed 283 overlapped genes. Centrality measures were calculated for these genes in the reconstructed STRING protein-protein interaction network. Applying LASSO logistic regression, eleven genes were ultimately recognized as candidate diagnostic genes. Among these genes, the area under the receiver operating characteristic curve (AUROC) values for nine genes (CDC25B, CDK4, IQGAP3, MMP1, MMP7, SLC7A5, TEAD4, TRIB3, and UHRF1) surpassed the threshold of 0.92 in both the training and validation sets. We evaluated the diagnostic performance of these genes with four machine learning algorithms: random forest (RF), support vector machines (SVM), artificial neural network (ANN), and gradient boosting machine (GBM). In the testing dataset (GSE21815 and GSE106582), the AUROC scores were greater than 0.95 for all of the machine learning algorithms, indicating the high diagnostic performance of the nine genes. Besides, these nine genes are also significantly correlated to twelve immune cells, namely Mast cells activated, Macrophages M0, M1, and M2, Neutrophils, T cells CD4 memory activated, T cells follicular helper, T cells CD8, T cells CD4 memory resting, B cells memory, Plasma cells, and Mast cells resting (P < 0.05). These results strongly suggest that all of the nine genes have the potential to serve as reliable diagnostic biomarkers for CRC., (© 2024. The Author(s).)

Prostate cancer is one of the most common cancers in men and poses a significant threat to global male health. Traditional prostate cancer assessment methods have certain limitations, necessitating the identification of new prognostic factors and treatment targets. Our study revealed that low expression of the cornichon family AMPA receptor auxiliary protein 2 (CNIH2) gene was associated with a better progression-free survival rate in prostate cancer patients. The area under the receiver operating characteristic (ROC) curve (AUC) showed that the prognostic ability of the CNIH2 gene was high at 1, 3, and 5 years. The gene was an independent prognostic factor according to multivariate analysis. Functional verification experiments showed that knocking down the CNIH2 gene could inhibit the proliferation, migration and invasion of prostate cancer cells and could also inhibit tumor growth in nude mice. Our study is the first to reveal the important role of the CNIH2 gene in prostate cancer. This discovery provides a new research direction for individualized treatment and prognostic evaluation of prostate cancer., (© 2024. The Author(s).)

The fragmentation patterns of cell-free DNA (cfDNA) in plasma can potentially be utilized as diagnostic biomarkers in liquid biopsy. However, our knowledge of this biological process and the information encoded in fragmentation patterns remains preliminary. Here, we investigated the cfDNA fragmentomic characteristics against nucleosome positioning patterns in hematopoietic cells. cfDNA molecules with ends located within nucleosomes were relatively shorter with altered end motif patterns, demonstrating the feasibility of enriching tumor-derived cfDNA in patients with cancer through the selection of molecules possessing such ends. We then developed three cfDNA fragmentomic metrics after end selection, which showed significant alterations in patients with cancer and enabled cancer diagnosis. By incorporating machine learning, we further built high-performance diagnostic models, which achieved an overall area under the curve of 0.95 and 85.1% sensitivity at 95% specificity. Hence, our investigations explored the end characteristics of cfDNA fragmentomics and their merits in building accurate and sensitive cancer diagnostic models., Competing Interests: Declaration of interests Y.A., J.J., and K.S. have filed patent applications based on the method developed in this work., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Cancer of women's reproductive organs (gynecological cancers) and breast cancer affect women all over the world [...].