GenVisR: Genomic Visualizations in R

Common bean pan-genome reveals abundant variation patterns and relationships of stress response genes and pathways

Long-term geographical isolation and the different directions of domestication can cause a large number of genome variations. Population genetic analysis based on a single reference genome cannot capture all the variation information. Pan-genome construction is an effective way to overcome this problem. Resequencing data from 683 common bean landraces and breeding lines provided a pan-genome construction data resource. For the first time, for common bean pan-genome construction, 305 Mb non-reference contigs and 10,452 novel genes were identified. Among these new genes, 373 resistance gene analogs containing 372 variable genes were identified and used to narrow down the candidate genes in Pseudomonas syringae pv. phaseolicola resistance quantitative trait locus interval of the common bean. Transcriptome analysis of multiple biotic and abiotic stresses reveals that gene expression patterns are organ-, stress-, and gene conservation-specific. Core and shell genes may be co-expressed in all samples and may have functional complementarity to maintain the stability of plant growth. Within pathways, 8990 and 30,272 mutual exclusivity and co-occurrence gene presence-absence variations (PAVs) were discovered respectively, providing further insights into the functional complementarity of genes. In conclusion, our study provides a comprehensive genome resource, which will be useful for further common bean breeding and study.

Molecular subtypes based on ferroptosis-related genes and tumor microenvironment infiltration characterization in small cell lung cancer

Background

Ferroptosis is an iron-dependent form of regulated cell death associated with cancer. However, the characteristics of ferroptosis in small cell lung cancer (SCLC) are still uncertain. This study aimed to explore the application value of ferroptosis-related genes (FRGs) classification in prognosis and characteristics prediction to provide clues for targeted SCLC therapy.

Method

We systematically characterized mRNA expression and genetic alterations of FRGs in SCLC, evaluating their expression pattern in 181 samples from 3 datasets. Unsupervised clustering analysis was performed to identify the molecular subtypes based on FRGs. We then conducted association analyses between FRG subtypes and various tumor microenvironment (TME) characteristics, traditional key transcript factor subtypes, clinical features, transcriptional and post-transcriptional regulation, drug response, and the efficacy of immunotherapy. Furthermore, the novel classification was validated in an independent cohort of 34 samples from Beijing.

Result

In this study, we identified three distinct ferroptosis subtypes in SCLC: S1, S2, and S3. We found that patients in S2 had the poorest prognosis. The FRG classification was correlated with the NOTCH pathway, MYC pathway, Neuroendocrine (NE), and epithelial-to-mesenchymal transition (EMT) process. Additionally, the FRG classification was strongly associated with TME 4 subtypes. To validate the classification, we employed an independent cohort. The FRG classification could also help to guide the prediction of chemical drugs. Finally, the heatmap showed the landscape of FRG subtypes, TME subtypes, NE subtypes, key transcription subtypes, age, gender, and stage.

Conclusion

Our identification of new SCLC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of SCLC.

Age-linked DNA methylation and gene expression patterns in parameningeal head and neck alveolar rhabdomyosarcoma reveal CDK9 as a promising therapeutic target

BACKGROUND

Alveolar rhabdomyosarcoma (ARMS) primarily affects children in the first decade of life, but it can also occur during adolescence, typically with a more favorable prognosis. This study aimed to explore differences in DNA methylation (DNAm) and gene expression profiles that may account for the worse prognosis in younger patients; and to investigate possible new therapeutic targets.

METHODS

We conducted whole-genome DNAm and transcriptome analyses on 10 parameningeal head and neck ARMS patients, including 4 patients under 1 year old and 6 over 10 years old. Among the differentially expressed genes, we focused on actionable therapeutic targets and confirmed their protein expression levels by immunohistochemistry. We validated the biological relevance of molecules of interest through functional experiments on rhabdomyosarcoma cell lines.

RESULTS

DNAm profiles did not significantly differ across age groups, while gene expression was the primary driver of observed differences. Several enriched pathways characterized younger patients with respect to older ones, including FAS, Integrin, PI3 kinase, and p53 by glucose deprivation. Among actionable molecules, cyclin dependent kinase 9 (CDK9) emerged as a promising therapy target, highly expressed in younger patients. Of note, CDK9 inhibitors specifically inhibit cell growth in bi- and three-dimensional ARMS cellular models, both as a monotherapy and in combination with BRD4 inhibitors.

CONCLUSION

Despite the small sample size, these findings suggest potential age-related molecular mechanisms and highlight candidate genes for further investigation as novel therapeutic targets. Notably, we identified CDK9 as a promising target, warranting further exploration in the context of ARMS treatment.

An immune cell activation signature reflected hepatocellular carcinoma heterogeneity and predicted clinical outcomes

Background

The prognosis of hepatocellular carcinoma (HCC) remains challenging, and immune activation plays a critical role in cancer treatment. Identifying reliable immune activation-related prognostic markers is critical for predicting HCC patient outcomes.

Method

A six-gene signature was developed. The prognostic value was assessed by correlating the signature and survival. The robustness of the signature was validated in three independent Gene Expression Omnibus (GEO) datasets. Associations with clinical, genomic, and transcriptomic features were also evaluated. Additionally, single-cell sequencing data were analyzed to explore cell-cell interaction heterogeneity reflected by the signature. The biological role of candidate gene RORC was investigated, including chemotherapy resistance and detailed regulatory mechanism in affecting progression. The clinical potential role of RORC and its downstream gene was also evaluated by immunohistochemical (IHC) microarray.

Results

The six-gene signature stratified patients into high-risk and low-risk groups, with high-risk samples exhibiting significantly shorter overall survival (median: 23.8 months, 95% CI: 20.6-41.8) than low-risk samples (median: 83.2 months, 95% CI: 69.6-NA, p < 0.001). Validation in independent GEO datasets confirmed the robustness of the signature. The signature was significantly associated with the pathological stage and negatively correlated with PD-L1 expression, outperforming clinical indicators in predicting 3-year survival. The signature was significantly associated with TP53 mutations, genomic stability, and canonical cancer-related pathways. Single-cell sequencing data indicated that the signature revealed cell-cell interaction heterogeneity in HCC. Candidate gene RORC promotes proliferation and migration by regulating CDC6 gene expression as a transcription factor. Furthermore, RORC is also associated with multiple drug resistance, especially docetaxel and paclitaxel. IHC revealed that RORC and candidate gene CDC6 were valuable predictive biomarkers for prognosis.

Conclusion

The six-gene signature provides valuable insights into the biological status of HCC patients and is a robust tool for clinical application.

CAN-Scan: A multi-omic phenotype-driven precision oncology platform identifies prognostic biomarkers of therapy response for colorectal cancer

Application of machine learning (ML) on cancer-specific pharmacogenomic datasets shows immense promise for identifying predictive response biomarkers to enable personalized treatment. We introduce CAN-Scan, a precision oncology platform, which applies ML on next-generation pharmacogenomic datasets generated from a freeze-viable biobank of patient-derived primary cell lines (PDCs). These PDCs are screened against 84 Food and Drug Administration (FDA)-approved drugs at clinically relevant doses (Cmax), focusing on colorectal cancer (CRC) as a model system. CAN-Scan uncovers prognostic biomarkers and alternative treatment strategies, particularly for patients unresponsive to first-line chemotherapy. Specifically, it identifies gene expression signatures linked to resistance against 5-fluorouracil (5-FU)-based drugs and a focal copy-number gain on chromosome 7q, harboring critical resistance-associated genes. CAN-Scan-derived response signatures accurately predict clinical outcomes across four independent, ethnically diverse CRC cohorts. Notably, drug-specific ML models reveal regorafenib and vemurafenib as alternative treatments for BRAF-expressing, 5-FU-insensitive CRC. Altogether, this approach demonstrates significant potential in improving biomarker discovery and guiding personalized treatments.

Construction and significance of a breast cancer prognostic model based on cuproptosis-related genotyping and lncRNAs

BACKGROUND/PURPOSE

Cuproptosis may play a significant role in breast cancer (BC). We aimed to investigate the prognostic impact of cuproptosis-related lncRNAs in BC.

METHODS

Consensus clustering analysis categorized TCGA-BRCA samples into 3 clusters, followed by survival and immune analyses of the 3 clusters. LASSO-COX analysis was performed on cuproptosis-related lncRNAs differentially expressed in BC to construct a BC prognostic model. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment, immune, and drug prediction analyses were performed on the high-risk and low-risk groups. Cell experiments were conducted to analyze the results of drug prediction and two cuproptosis-related lncRNAs (AC104211.1 and LINC01863).

RESULTS

Significant differences were observed in survival outcomes and immune infiltration levels among the three clusters (p < 0.05). The validation of the model showed significant differences in survival outcomes between the high-risk and low-risk groups in both the training and validation sets (p < 0.05). Differential mRNAs between the two groups were significantly enriched in the Neuroactive ligand-receptor interaction and cAMP signaling pathway. Additionally, significant differences were found in immune infiltration levels, human leukocyte antigen (HLA) expression, Immunophenoscore (IPS) scores, and Tumor Immune Dysfunction and Exclusion (TIDE) scores between the two groups (p < 0.05). Drug prediction and corresponding cell experimental results showed that Trametinib, 5-fluorouracil, and AICAR significantly inhibited the viability of MCF-7 cells (p < 0.05). AC104211.1 and LINC01863 were found to impact the proliferation of BC cells.

CONCLUSION

The risk-scoring model obtained in this study may serve as a robust prognostic biomarker, potentially aiding in clinical decision-making for BC patients.

GATA6 Amplification Is Associated With Improved Survival in TP53-Mutated Unresectable Pancreatic Cancer

OBJECTIVES

GATA6 expression is recognized as a favorable prognostic marker of pancreatic cancer, whereas TP53 is a poor prognostic marker. We evaluated treatment outcomes by genetic alterations in TP53 and GATA6 to determine the prognostic and predictive impact of co-alterations.

MATERIALS AND METHODS

A single institution retrospective analysis was performed on patients diagnosed with pancreatic ductal adenocarcinoma between 2014 and 2023. TP53 genotype and GATA6 amplification status were included in an analysis of overall survival (OS) and progression-free survival (PFS). Previously published patient-derived organoids were used to investigate correlation between genetic status and drug sensitivity.

RESULTS

Patients with TP53 mutations had worse OS compared with the wild-type TP53 population. Patients with GATA6 amplification had better OS and a trend toward better PFS than the nonamplified population. Among patients with a TP53 mutation, patients with GATA6 co-alteration had longer OS compared with those who were not GATA6 amplified. In contrast, among patients who were TP53 wild-type, the presence or absence of a GATA6 amplification did not impact OS or PFS. GATA6 genotype was not associated chemotherapy drug response in an organoid pharmacotyping model.

CONCLUSIONS

We found that GATA6 amplification appeared to attenuate poor prognosis observed in TP53-mutant patients regardless of the type of standard chemotherapy received, suggesting the GATA6 amplification is a prognostic biomarker but not a predictive biomarker of standard-of-care chemotherapy.

Identification and analysis of amino acid metabolism-related subtypes in lung adenocarcinoma

We aimed to explore the role of amino acid metabolism (AAM) and identify biomarkers for prognosis management and treatment of lung adenocarcinoma. Differentially expressed genes (DEGs) associated with AAM in lung adenocarcinoma were selected from public databases. Samples were clustered into varying subtypes using ConsensusClusterPlus based on gene levels. Survival analysis was conducted using a survival package, and immune analysis was performed using ssGSEA and ESTIMATE. Enrichment analysis was performed using gene set enrichment analysis, and a protein-protein interaction network of DEGs between subgroups was established through STRING. Hub genes were screened and verified using survival analysis, and drug sensitivity prediction was performed. One hundred sixty-three DEGs associated with AAM in lung adenocarcinoma were obtained, and two AAM-associated subtypes were identified. Cluster 1 showed higher survival rates and immune levels compared with cluster 2. The two subtypes were mainly enriched in immune-related signaling pathways, such as B cell receptor, Jak-Stat, and natural killer cell-mediated cytotoxicity. In addition, the mutation landscape between the two groups was significantly different. F2, AHSG, and APOA1 were key hub genes that significantly affected the prognosis differences between the two subtypes. Cluster 2 showed higher sensitivity to drugs, such as mithramycin, depsipeptide, and actinomycin than cluster 1. This study identified two AAM-associated gene subtypes and their biomarkers and predicted the immune status and drug treatment sensitivity of varying subtypes. The results are instructive in the clinical treatment of lung adenocarcinoma.NEW & NOTEWORTHY Two amino acid metabolism-related subtypes were identified based on differentially expressed genes associated with amino acid metabolism. Cluster 1 showed higher survival rates and immune levels compared with cluster 2. Cluster 2 showed higher sensitivity to drugs, such as mithramycin, depsipeptide, and actinomycin compared with cluster 1.

A novel mouse model of upper tract urothelial carcinoma highlights the impact of dietary intervention on gut microbiota and carcinogenesis prevention despite carcinogen exposure

Animal models of N-butyl-N-(4-hydroxy butyl) nitrosamine (BBN)-induced urothelial carcinoma (UC), particularly bladder cancer (BC), have long been established. However, the rare incidence of BBN-induced upper urinary tract UC (UTUC), which originates from the same urothelium as BC, remains elusive. The scarcity of animal models of UTUC has made it challenging to study the biology of UTUC. To address this problem, we tried to establish a novel mouse model of UTUC by treating multiple mice strains and sexes with BBN. The molecular consistency between the UTUC mouse model and human UTUC was confirmed using multi-omics analyses, including whole-exome, whole-transcriptome, and spatial transcriptome sequencing. 16S ribosomal RNA metagenome sequencing, metabolome analysis, and dietary interventions were employed to assess changes in the gut microbiome, metabolome, and carcinogenesis of UTUC. Of all treated mice, only female BALB/c mice developed UTUC over BC. Multi-omics analyses confirmed that the UTUC model reflected the molecular characteristics and heterogeneity of human UTUC with poor prognosis. Furthermore, the model exhibited increased Tnf-related inflammatory gene expression in the upper urinary tract and a low relative abundance of Parabacteroides distasonis in the gut. Dietary intervention, mainly without alanine, led to P. distasonis upregulation and successfully prevented UTUC, as well as suppressed Tnf-related inflammatory gene expression in the upper urinary tract despite the exposure to BBN. This is the first report to demonstrate a higher incidence of UTUC than BC in a non-engineered mouse model using BBN. Overall, this model could serve as a useful tool for comprehensively investigating UTUC in future studies.

Identification and validation of mitochondrial endoplasmic reticulum membrane-related genes in atherosclerosis

The mitochondria-associated endoplasmic reticulum membrane is implicated in atherosclerosis (AS). However, its precise molecular mechanisms remain undefined. This study identified KLRC1 and SOCS2 as key protective genes against AS through transcriptomic analysis integrated with Mendelian randomization. Both genes exhibited significantly reduced expression in the AS group. Immune infiltration analysis revealed a strong positive correlation between activated CD8+ T cells and these genes, while eosinophils displayed the most pronounced negative correlation with KLRC1, and regulatory T cells exhibited the strongest negative association with SOCS2. Notably, SOCS2 emerged as a pivotal protective factor, offering novel insights into AS pathogenesis and providing a robust theoretical foundation for early diagnosis and potential therapeutic strategies.

Coding and regulatory somatic profiling of triple-negative breast cancer in Sub-Saharan African patients

The burden of triple-negative breast cancer (TNBC) may be shaped by genetic factors, particularly inherited and somatic mutation profiles. However, data on this topic remain limited, especially for the African continent, where a higher TNBC incidence is observed. In the age of precision medicine, cataloguing TNBC diversity in African patients becomes imperative. We performed whole exome sequencing, including untranslated regions, on 30 samples from Angola and Cape Verde, which allowed to ascertain on potential regulatory mutations in TNBC for the first time. A high somatic burden was observed for the African cohort, with 86% of variants being so far unreported. Recurring to predictive functional algorithms, 17% of the somatic single nucleotide variants were predicted to be deleterious at the protein level, and 20% overlapped with candidate cis-regulatory elements controlling gene expression. Several of these somatic functionally-impactful mutations and copy number variation (mainly in 1q, 8q, 6 and 10p) occur in known BC- and all cancer-driver genes, enriched for several cancer mechanisms, including response to radiation and related DNA repair mechanisms. TP53 is the top of these known BC-driver genes, but our results identified possible novel TNBC driver genes that may play a main role in the African context, as TTN, CEACAM7, DEFB132, COPZ2 and GAS1. These findings emphasize the need to expand cancer omics screenings across the African continent, the region of the globe with highest genomic diversity, accelerating the discovery of new somatic mutations and cancer-related pathways.

Brain metastases lung adenocarcinoma patients with BRG1 loss have a grim prognosis, featuring unique morphological and methylation characteristics

BRG1 deficiency in patients with lung adenocarcinoma that has metastasized to the brain, termed BRG1-deficient brain metastasis lung adenocarcinoma, is an uncommon event. Prior to this study, these patients had not undergone extensive molecular and (epi)genetic analysis. We report a comprehensive clinical, histopathologic, and molecular assessment of 9 BRG1-deficient brain metastasis lung adenocarcinoma cohort (BRG1-deficient BM cohort) in comparison with a 16 BRG1-retained brain metastasis lung adenocarcinoma cohort (BRG1-retained BM cohort). Patients with BRG1-deficient BM exhibited a significantly increased risk of mortality. Molecular analysis revealed a high prevalence of mutations in SMARCA4 and TP53 genes within this group. DNA methylation molecular diagnostics showed a high rate of genomic instability and a markedly lower DNA methylation age in these patients. Functional enrichment analysis of differentially methylated genes suggested that hypomethylation genes were primarily associated with the negative regulation of neuron differentiation, G protein-coupled receptor signaling pathways, and cell differentiation. Conversely, hypermethylation was linked to the regulation of small GTPase mediated signal transduction, Rho protein signal transduction, DNA damage response, and apoptotic processes. This study investigated a rare subgroup of lung adenocarcinoma patients with brain metastasis characterized by BRG1 deficiency and a poor prognosis. Our study not only provides a comprehensive multi-omic data resource but also provides valuable biological insights into patients. The findings may serve as a valuable reference for the future pathological diagnosis of BRG1-deficient brain metastasis in lung adenocarcinoma patients.

Alternative driver pathways in peripheral nerve sheath tumors - including DICER1 and/or KRAS alterations

DICER1-associated sarcoma is an emerging entity, defined by either somatic or germline dicer 1, ribonuclease III (DICER1) mutations and sharing characteristic morphologic features irrespective of the site of origin. In addition to the DICER1 driver mutation, concurrent genomic alterations, including tumor protein 53 (TP53) inactivation and RAS pathway activation, are frequently detected. Tumors that morphologically resemble malignant peripheral nerve sheath tumor (MPNST) have rarely been reported among DICER1 sarcomas and often pose diagnostic challenges. This study was prompted by a case involving morphologic features of MPNST, which harbored co-existing DICER1 and hotspot KRAS mutations. Hence, we investigated the incidence of these alterations in PNST from our molecular database compared to the genomic and morphologic spectrum of DICER1-mutant sarcomas. In total, we identified three cases diagnosed as MPNST with co-existing DICER1, ATRX chromatin remodeler (ATRX), and KRAS G12V/A alterations occurring in brain, cerebellopontine angle, and intra-abdominal sites. Two additional cases each of MPNSTs and neurofibromas were identified with hotspot KRAS mutations. All five MPNSTs lacked canonical neurofibromin 1 (NF1)/neurofibromin 2 (NF2) alterations, displaying a classic morphologic appearance with fascicular monomorphic spindle cells and followed a diverse clinical behavior. Among the 38 DICER1-associated sarcomas in our database, eight (21%) had secondary KRAS hotspot mutations, all composed of monomorphic spindle and/or round cells, including three with an MPNST-like histology. In contrast, all 10 (26%) DICER1-mutant sarcomas with TP53 mutations showed a pleomorphic phenotype. The DNA-based methylation profile of our index case clustered within the group of sarcomas with DICER1 alterations. Our results highlight a small subset of MPNST associated with DICER1 and/or KRAS mutations. However, their relationship with conventional MPNST remains to be determined in larger studies. © 2025 The Pathological Society of Great Britain and Ireland.

Refined variant calling pipeline on RNA-seq data of breast cancer cell lines without matched-normal samples

OBJECTIVE

RNA-seq delivers valuable insights both to transcriptional patterns and mutational landscapes for transcribed genes. However, as tumour cell lines frequently lack their matched-normal counterpart, variant calling without the paired normal sample is still challenging. In order to exclude variants of common genetic variation without a matched-normal control, filtering strategies need to be developed to identify tumour relevant variants in cell lines.

RESULTS

Here, variants of 29 breast cancer cell lines were called on RNA-seq data via HaplotypeCaller. Low read depth sites, RNA-edit sites, and low complexity regions in coding regions were excluded. Common variants were filtered using 1000 genomes, gnomAD, and dbSNP data. Starting from hundred thousands of single nucleotide variants and small insertions and deletions, about thousand variants remained after filtering for each sample. Extracted variants were validated against the Catalogue of Somatic Mutations in Cancer (COSMIC) for 10 cell lines included in both data sets. Approximately half of the COSMIC variants were successfully called. Importantly, missing variants could mainly be attributed to sites with low read depth. Moreover, filtered variants also included all 10 cancer gene census COSMIC variants, a condensed hallmark variant set.

Pharmacoproteogenomic approach identifies on-target kinase inhibitors for cancer drug repositioning

Drug repositioning of approved drugs offers advantages over de novo drug development for a rare type of cancer. To efficiently identify on-target drugs from clinically successful kinase inhibitors in cancer drug repositioning, drug screening and molecular profiling of cell lines are essential to exclude off-targets. We developed a pharmacoproteogenomic approach to identify on-target kinase inhibitors, combining molecular profiling of genomic features and kinase activity, and drug screening of patient-derived cell lines. This study examined eight patient-derived giant cell tumor of the bone (GCTB) cell lines, all of which harbored a signature mutation of H3-3A but otherwise without recurrent copy number variants and mutations. Kinase activity profiles of 100 tyrosine kinases with a three-dimensional substrate peptide array revealed that nine kinases were highly activated. Pharmacological screening of 60 clinically used kinase inhibitors found that nine drugs directed at 29 kinases strongly suppressed cell viability. We regarded ABL1, EGFR, and LCK as on-target kinases; among the two corresponding on-target kinase inhibitors, osimertinib and ponatinib emerged as on-target drugs whose target kinases were significantly activated. The remaining 26 kinases and seven kinase inhibitors were excluded as off-targets. Our pharmacoproteomic approach enabled the identification of on-target kinase inhibitors that are useful for drug repositioning.

SAMURAI: shallow analysis of copy number alterations using a reproducible and integrated bioinformatics pipeline

Shallow whole-genome sequencing (sWGS) offers a cost-effective approach to detect copy number alterations (CNAs). However, there remains a gap for a standardized workflow specifically designed for sWGS analysis. To address this need, in this work we present SAMURAI, a bioinformatics pipeline specifically designed for analyzing CNAs from sWGS data in a standardized and reproducible manner. SAMURAI is built using established community standards, ensuring portability, scalability, and reproducibility. The pipeline features a modular design with independent blocks for data preprocessing, copy number analysis, and customized reporting. Users can select workflows tailored for either solid or liquid biopsy analysis (e.g. circulating tumor DNA), with specific tools integrated for each sample type. The final report generated by SAMURAI provides detailed results to facilitate data interpretation and potential downstream analyses. To demonstrate its robustness, SAMURAI was validated using simulated and real-world data sets. The pipeline achieved high concordance with ground truth data and maintained consistent performance across various scenarios. By promoting standardization and offering a versatile workflow, SAMURAI empowers researchers in diverse environments to reliably analyze CNAs from sWGS data. This, in turn, holds promise for advancements in precision medicine.

Pangenome Data Analysis Reveals Characteristics of Resistance Gene Analogs Associated with Sclerotinia sclerotiorum Resistance in Sunflower

The sunflower, an important oilseed crop and food source across the world, is susceptible to several pathogens, which cause severe losses in sunflower production. The utilization of genetic resistance is the most economical, effective measure to prevent infectious diseases. Based on the sunflower pangenome, in this study, we explored the variability of resistance gene analogs (RGAs) within the species. According to a comparative analysis of RGA candidates in the sunflower pangenome using the RGAugury pipeline, a total of 1344 RGAs were identified, comprising 1107 conserved, 199 varied, and 38 rare RGAs. We also identified RGAs associated with resistance against Sclerotinia sclerotiorum (S. sclerotiorum) in sunflower at the quantitative trait locus (QTL). A total of 61 RGAs were found to be located at four quantitative trait loci (QTLs). Through a detailed expression analysis of RGAs in one susceptible and two tolerant sunflower inbred lines (ILs) across various time points post inoculation, we discovered that 348 RGAs exhibited differential expression in response to Sclerotinia head rot (SHR), with 17 of these differentially expressed RGAs being situated within the QTL regions. In addition, 15 RGA candidates had gene introgression. Our data provide a better understanding of RGAs, which facilitate genomics-based improvements in disease resistance in sunflower.

A Comprehensive Clinicopathologic and Molecular Reappraisal of GLI1 -altered Mesenchymal Tumors with Pooled Outcome Analysis Showing Poor Survival in GLI1 - amplified Versus GLI1- rearranged Tumors

GLI1 -altered mesenchymal tumor is a recently described distinct pathologic entity with an established risk of malignancy, being defined molecularly by either GLI1 gene fusions or amplifications. The clinicopathologic overlap of tumors driven by the 2 seemingly distinct mechanisms of GLI1 activation is still emerging. Herein, we report the largest series of molecularly confirmed GLI1 -altered mesenchymal neoplasms to date, including 23 GLI1- amplified and 15 GLI1 -rearranged new cases, and perform a comparative clinicopathologic, genomic, and survival investigation. GLI1- rearranged tumors occurred in younger patients (42 vs. 52 y) and were larger compared with GLI1 -amplified tumors (5.6 cm vs. 1.5 cm, respectively). Histologic features were overall similar between the 2 groups, showing a multinodular pattern and a nested architecture of epithelioid, and less commonly spindle cells, surrounded by a rich capillary network. A distinct whorling pattern was noted among 3 GLI1 -amplified tumors. Scattered pleomorphic giant cells were rarely seen in both groups. The immunoprofile showed consistent expression of CD56, with variable S100, CD10 and SMA expression. Genomically, both groups had overall low mutation burdens, with rare TP53 mutations seen only in GLI1- amplified tumors. GLI1 -amplified mesenchymal tumors exhibit mostly a single amplicon at the 12q13-15 locus, compared with dedifferentiated liposarcoma, which showed a 2-peak amplification centered around CDK4 (12q14.1) and MDM2 (12q15). GLI1 -amplified tumors had a significantly higher GLI1 mRNA expression compared with GLI1 -rearranged tumors. Survival pooled analysis of current and published cases (n=83) showed a worse overall survival in GLI1 -amplified patients, with 16% succumbing to disease compared with 1.7% in the GLI1- rearranged group. Despite comparable progression rates, GLI1 -amplified tumors had a shorter median progression-free survival compared with GLI1 -rearranged tumors (25 mo vs. 77 mo). Univariate analysis showed that traditional histologic predictors of malignancy (mitotic count ≥4/10 high-power fields, presence of necrosis, and tumor size ≥5 cm) are associated with worse prognosis among GLI1 -altered mesenchymal tumors.

Transcription Factor E2F4 Promote Proliferation, Migration, and Invasion of Gastric Cancer Cells by transcriptionally activating DSCC1

Gastric cancer (GC) ranks as the fifth most common cancer and the fourth leading cause of cancer-related deaths globally. Despite advancements in molecular profiling, the mechanisms driving GC proliferation and metastasis remain unclear. This study identifies Early 2 Factor 4 (E2F4) as a key transcription factor that promotes GC cell proliferation, migration, and invasion by upregulating DNA Replication and Sister Chromatid Cohesion 1 (DSCC1) expression. Bioinformatics and transcription factor analyses revealed E2F4 as a significant regulator of DSCC1. Functional assays confirmed E2F4's role in enhancing GC cell malignancy in vitro and in vivo. Knockdown and overexpression experiments demonstrated that E2F4 positively regulates DSCC1 at the transcriptional level, with ChIP-qPCR and dual luciferase reporter assays validating the binding sites on the DSCC1 promoter. These findings highlight the E2F4-DSCC1 axis as a potential therapeutic target to mitigate GC progression.

Clinical Significance and Molecular Annotation for PD-L1 Negative Advanced Non-Small Cell Lung Cancer with Sensitivity to Responsive to Dual PD-1/CTLA-4 Blockade

Background

Immunotherapy has become the standard treatment for driving gene-negative advanced non-small cell lung cancer (NSCLC). However, compared to PD-L1-positive patients, the efficacy of Anti-PD-(L)1 monotherapy is suboptimal in PD-L1-negative advanced NSCLC. In this study, we aim to analyze the optimal immunotherapy approach for PD-L1-negative NSCLC patients and develop a new nomogram to enhance the clinical predictability of immunotherapy for NSCLC patients.

Methods

In this study, we retrieved clinical information and genomic data from cBioPortal for NSCLC patients undergoing immunotherapy. Cox regression analyses were utilized to screen the clinical information and genomic data that related to survival. The prognostic-relate genes function was studied by comprehensive bioinformatics analyses. The Kaplan-Meier plot method was employed for survival analysis.

Results

A total of 199 PD-L1-negative NSCLC patients were included in this study. Among them, 165 patients received Anti-PD-(L)1 monotherapy, while 34 patients received Anti-PD-(L)1+Anti-CTLA-4 combination therapy. The Anti-PD-(L)1+Anti-CTLA-4 combination therapy demonstrated significantly higher PFS compared to the Anti-PD-(L)1 monotherapy. The mutation status of KRAS, ANO1, COL14A1, LTBP1. ERBB4 and PCSK5 were found to correlate with PFS. Utilizing the clinicopathological parameters and genomic data of the patients, a novel nomogram was developed to predict the prognosis of Anti-PD-(L)1+Anti-CTLA-4 combination therapy.

Conclusion

Our study revealed that KRAS, ANO1, COL14A1, LTBP1. ERBB4 and PCSK5 mutation could serve as predictive biomarkers for patients with Anti-PD-(L)1+Anti-CTLA-4 combination therapy. Our systematic nomogram demonstrates significant potential in predicting the prognosis for NSCLC patients with responsive to dual PD-1/CTLA-4 blockade.

A new TGF-β risk score predicts clinical and immune landscape in colorectal cancer patients

Background

Aberrant TGF-β signaling pathway can lead to invasive phenotype of colorectal cancer (CRC), resulting in poor prognosis. It is pivotal to develop an effective prognostic factor on the basis of TGF-β-related genes to accurately identify risk of CRC patients.

Methods

We performed differential analysis of TGF-β-related genes in CRC patients from databases and previous literature to obtain TGF-β-related differentially expressed genes (TRDEGs). LASSO-Cox regression was utilized to build a CRC prognostic feature model based on TRDEGs. The model was validated using two GEO validation sets. Wilcoxon rank-sum test was utilized to test correlation of model with clinical factors. ESTIMATE algorithm and ssGSEA and tumor mutation burden (TMB) analysis were used to analyze immune landscape and mutation burden of high-risk (HR) and low-risk (LR) groups. CellMiner database was utilized to identify therapeutic drugs with high sensitivity to the feature genes.

Results

We established a six-gene risk prognostic model with good predictive accuracy, which independently predicted CRC patients' prognoses. The HR group was more likely to experience immunotherapy benefits due to higher immune infiltration and TMB. The feature gene TGFB2 could inhibit the efficacy of drugs such as XAV-939, Staurosporine, and Dasatinib, but promote the efficacy of drugs such as CUDC-305 and by-product of CUDC-305. Similarly, RBL1 could inhibit the drug action of Fluphenazine and Imiquimod but promote that of Irofulven.

Conclusion

A CRC risk prognostic signature was developed on basis of TGF-β-related genes, which provides a reference for risk and further therapeutic selection of CRC patients.

Multi-omics analysis identifies repurposing bortezomib in the treatment of kidney-, nervous system-, and hematological cancers

Repurposing of FDA-approved drugs is a quick and cost-effective alternative to de novo drug development. Here, we identify genes involved in bortezomib sensitivity, predict cancer types that may benefit from treatment with bortezomib, and evaluate the mechanism-of-action of bortezomib in breast cancer (BT-474 and ZR-75-30), melanoma (A-375), and glioblastoma (A-172) cells in vitro. Cancer cell lines derived from cancers of the blood, kidney, nervous system, and skin were found to be significantly more sensitive to bortezomib than other organ systems. The in vitro studies confirmed that although bortezomib effectively inhibited the β5 catalytic site in all four cell lines, cell cycle arrest was only induced in G2/M phase and apoptosis in A-375 and A-172 after 24h. The genomic and transcriptomic analyses identified 33 genes (e.g. ALDH18A1, ATAD2) associated with bortezomib resistance. Taken together, we identified biomarkers predictive of bortezomib sensitivity and cancer types that might benefit from treatment with bortezomib.

Detection of HBV DNA integration in plasma cell-free DNA of different HBV diseases utilizing DNA capture strategy

The landscape of hepatitis B virus (HBV) integration in the plasma cell-free DNA (cfDNA) of HBV-infected patients with different stages of liver diseases [chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC)] remains unclear. In this study, we developed an improved strategy for detecting HBV DNA integration in plasma cfDNA, based on DNA probe capture and next-generation sequencing. Using this optimized strategy, we successfully detected HBV integration events in chimeric artificial DNA samples and HBV-infected HepG2-NTCP cells at day one post infection, with high sensitivity and accuracy. The characteristics of HBV integration events in the HBV-infected HepG2-NTCP cells and plasma cfDNA from HBV-infected individuals (CHB, LC, and HCC) were further investigated. A total of 112 and 333 integration breakpoints were detected in the HepG2-NTCP cells and 22 out of 25 (88%) clinical HBV-infected samples, respectively. In vivo analysis showed that the normalized number of support unique sequences (nnsus) in HCC was significantly higher than in CHB or LC patients (P values ​< ​0.05). All integration breakpoints are randomly distributed on human chromosomes and are enriched in the HBV genome around nt 1800. The majority of integration breakpoints (61.86%) are located in the gene-coding region. Both non-homologous end-joining (NHEJ) and microhomology-mediated end-joining (MMEJ) interactions occurred during HBV integration across the three different stages of liver diseases. Our study provides evidence that HBV DNA integration can be detected in the plasma cfDNA of HBV-infected patients, including those with CHB, LC, or HCC, using this optimized strategy.

A pilot study of childhood-onset Takayasu arteritis using whole exome sequencing suggests oligogenic inheritance involving classical complement, collagen, and autoinflammatory pathways

Takayasu arteritis (TA) is a chronic granulomatous inflammatory disease affecting the aorta and its branches. Paediatric TA (pTA) may present from 6 months after birth till the adolescent age group. Genetics and pathogenesis of pTA are not fully understood. Earlier studies reported monogenic mutation in NOD2, XIAP, and STAT1 genes in patients with pTA. TA, a relatively rare disease, is more common in geographical pockets, including India. We hypothesized that South Asian patients with pTA, namely, those of Indian subcontinent origin, may have clinically relevant and unique pathogenic variants involving one or more genes, especially those linked to genetically driven vasculitic illnesses, including autoinflammatory pathologies. Children with pTA fulfilling EULAR/PRINTO/PReS classification criteria and presenting with clinical symptoms to the Paediatric Rheumatology clinic of Christian Medical College, Vellore, were included. Blood samples were collected after getting informed consent from parents or guardians and assent forms from children. DNA was extracted from whole blood using the Qiagen DNA extraction kit. Initially, the common variant in Indian population, namely, ADA2 c.139G > A; p.Gly47Arg, was screened, followed by whole exome sequencing. Fourteen children were recruited for the study. Median age of patients was 11 years (4 months-14 years) with a male-to-female ratio of 4:10. Distribution of angiographic subsets by Numano's classification of included children were as follows: type 5 (n = 7), type 4 (n = 5), and type 3 (n = 2). We identified novel variants in ten different genes. This include variants in genes of classical complement pathway, namely, C2, C3, C6, C7, and C9, and other genes, namely, CYBA, SH3BP2, GUCY2C, CTC1, COL5A1, and NLPR3. Two of 14 patients have heterozygous pathogenic variants; this implies that combination of heterozygous variants in C3 and COL5A1 might lead to disease development, suggesting digenic inheritance. One patient has a homozygous variant in CYBA. None of the patients were identified to have ADA2 variants. Whole exome sequencing reveals combination of rare variants in genes C3, COL5A1, and CYBA associated with disease development in children with Takayasu Arteritis. Key Points • We identified novel variants in genes of classical complement pathway, namely, C2, C3, C6, C7, and C9, and other genes, namely, CYBA, SH3BP2, GUCY2C, CTC1, COL5A1, and NLPR3. • Two of 14 patients have heterozygous pathogenic variants in C3 and COL5A1; this may have implications in disease development, suggesting digenic inheritance. • One patient has homozygous variant in CYBA. • None of the patients were identified to have ADA2 variants.

Integrated single-cell and bulk RNA sequencing revealed an epigenetic signature predicts prognosis and tumor microenvironment colorectal cancer heterogeneity

BACKGROUND

Colorectal cancer (CRC) prognosis prediction is currently a major challenge. Epigenetic regulation has been widely reported for its role in cancer development.

AIM

To construct a robust prognostic signature, we used developed and validated across datasets.

METHODS

After constructing the signature, the prognostic value of the signature was evaluated in the TCGA cohort and six independent datasets (GSE17526, GSE17537, GSE33113, GSE37892, GSE39048 and GSE39582). The clinical, genomic and transcriptomic features related to the signature were identified. The correlations of the signature score with immune cell infiltration and cell-cell interactions were analyzed. The correlations between the signature score and the sensitivity to different drugs were also predicted.

RESULTS

In the TCGA cohort, patients in the low-risk group according to the signature score had longer survival than those in the high-risk group, and this finding was validated in the validation datasets. The signature was a prognostic factor independent of age and sex and was correlated with stage and PD-1/PD-L1 expression. Area under the receiving operating characteristic curve was 0.72. Genomic association analyses revealed that samples from high-risk patients exhibited chromosomal instability. Transcriptomic analyses revealed that the signature score was significantly associated with multiple cellular pathways. Bulk RNA-seq and single-cell sequencing data revealed that the signature reflected differences in infiltrating immune cell-tumor cell interactions, especially for macrophages. The signature also predicted the putative drug sensitivity of CRC samples.

CONCLUSION

The signature is a valuable biomarker for predicting CRC prognosis and reflects multiple features of CRC, especially macrophage infiltration in the microenvironment.

Molecular subtype identification and prognosis stratification by a immunogenic cell death-related gene expression signature in colorectal cancer

OBJECTIVES

This study intended to develop a new immunogenic cell death (ICD)-related prognostic signature for colorectal cancer (CRC) patients.

RESEARCH DESIGN AND METHODS

The Non-Negative Matrix Factorization (NMF) algorithm was adopted to cluster tumor samples based on ICD gene expression to obtain ICD-related subtypes. Survival analysis and immune microenvironment analysis were conducted among different subtypes. Regression analysis was used to construct the model. Based on riskscore median, cancer patients were classified into high and low risk groups, and independent prognostic ability of the model was analyzed. The CIBERSORT algorithm was adopted to determine the immune infiltration level of both groups.

RESULTS

We analyzed the differential genes between cluster 4 and cluster 1-3 and obtained 12 genes with the best prognostic features finally (NLGN1, SLC30A3, C3orf20, ADAD2, ATOH1, ATP6V1B1, KCNQ2, MUCL3, RGCC, CLEC17A, COL6A5, and INSL4). In addition, patients with lower risk had higher levels of infiltration of most immune cells, lower Tumor Immune Dysfunction and Exclusion (TIDE) level and higher immunophenscore (IPS) level than those with higher risk.

CONCLUSIONS

This study constructed and validated the ICD feature signature predicting CRC prognosis and provide a reference criteria for guiding the prognosis and immunotherapy of CRC cancer patients.

Identification of lung adenocarcinoma subtypes based on mitochondrial energy metabolism-related genes

BACKGROUND

Identifying subtypes of lung adenocarcinoma (LUAD) patients based on mitochondrial energy metabolism and immunotherapy sensitivity is essential for precision cancer treatment.

METHODS

LUAD subtypes were identified using unsupervised consensus clustering, and results were subjected to immune and tumor mutation analyses. DEGs between subtypes were identified by differential analysis. Functional enrichment and PPI network analyses were conducted. Patients were classified into high and low expression groups based on the expression of the top 10 hub genes, and survival analysis was performed. Drugs sensitive to feature genes were screened based on the correlation between hub gene expression and drug IC50 value. qRT-PCR and western blot were used for gene expression detection, and CCK-8 and flow cytometry were for cell viability and apoptosis analysis.

RESULTS

Cluster-1 had significantly higher overall survival and a higher degree of immunoinfiltration and immunophenotypic score, but a lower TIDE score, DEPTH score, and TMB. Enrichment analysis showed that pathways and functions of DEGs between two clusters were mainly related to the interaction of receptor ligands with intracellular proteases. High expression of hub genes corresponded to lower patient survival rates. The predicted drugs with high sensitivity to feature genes were CDK1: Ribavirin (0.476), CCNB2: Hydroxyurea (0.474), Chelerythrine (0.470), and KIF11: Ribavirin (0.471). KIF11 and CCNB2 were highly expressed in LUAD cells and promoted cell viability and inhibited cell apoptosis.

CONCLUSION

This study identified two subtypes of LUAD, with cluster-1 being more suitable for immunotherapy. These results provided a reference for the development of precision immunotherapy for LUAD patients.

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV

Prostate cancer lineage plasticity is a key driver in the transition to neuroendocrine prostate cancer (NEPC), and the RTK/RAS signaling pathway is a well-established cancer pathway. Nevertheless, the comprehensive link between the RTK/RAS signaling pathway and lineage plasticity has received limited investigation. In particular, the intricate regulatory network governing the interplay between RTK/RAS and lineage plasticity remains largely unexplored. The multi-omics data were clustered with the coefficient of argument and neighbor joining algorithm. Subsequently, the clustered results were analyzed utilizing the GSEA, gene sets related to stemness, multi-lineage state datasets, and canonical cancer pathway gene sets. Finally, a comprehensive exploration of the data based on the ssGSEA, WGCNA, GSEA, VIPER, prostate cancer scRNA-seq data, and the GPSAdb database was conducted. Among the six modules in the clustering results, there are 300 overlapping genes, including 3 previously unreported prostate cancer genes that were validated to be upregulated in prostate cancer through RT-qPCR. Function Module 6 shows a positive correlation with prostate cancer cell stemness, multi-lineage states, and the RTK/RAS signaling pathway. Additionally, the 19 leading-edge genes of the RTK/RAS signaling pathway promote prostate cancer lineage plasticity through a complex network of transcriptional regulation and copy number variations. In the transcriptional regulation network, TP63 and FOXO1 act as suppressors of prostate cancer lineage plasticity, whereas RORC exerts a promoting effect. This study provides a comprehensive perspective on the role of the RTK/RAS pathway in prostate cancer lineage plasticity and offers new clues for the treatment of NEPC.

Colorectal cancer subtyping and immune landscape analysis based on natural killer cell-related genes

BACKGROUND AND STUDY AIMS

The prognosis of colorectal cancer (CRC) is related to natural killer (NK) cells, but the molecular subtype features of CRC based on NK cells are still unknown. This study aimed to identify NK cell-related molecular subtypes of CRC and analyze the survival status and immune landscape of patients with different subtypes.

PATIENTS/MATERIAL AND METHODS

mRNA expression data, single nucleotide variant (SNV) data, and clinical information of CRC patients were obtained from The Cancer Genome Atlas. Differentially expressed genes (DEGs) were obtained through differential analysis, and the intersection was taken with NK cell-associated genes to obtain 103 NK cell-associated CRC DEGs (NCDEGs). Based on NCDEGs, CRC samples were divided into three clusters through unsupervised clustering analysis. Survival analysis, immune analysis, Gene Set Enrichment Analysis (GSEA), and tumor mutation burden (TMB) analysis were performed. Finally, NCDEG-related small-molecule drugs were screened using the CMap database.

RESULTS

Survival analysis revealed that cluster2 had a lower survival rate than cluster1 and cluster3 (p < 0.05). Immune infiltration analysis found that the immune infiltration levels and immune checkpoint expression levels of cluster1_3 were substantially higher than those of cluster2, and the tumor purity was the opposite (p < 0.05). GSEA presented that cluster1_3 was significantly enriched in the chemokine signaling pathway, ECM receptor interaction, and antigen processing and presentation pathways (p < 0.05). The TMB of cluster1_3 was significantly higher than that of cluster2 (p < 0.05). Genes with the highest mutation rate in CRC were APC, TP53, TTN, and KRAS. Drug prediction results showed that small-molecule drugs that reverse the upregulation of NCDEGs, deoxycholic acid, dipivefrine, phenformin, and other drugs may improve the prognosis of CRC.

CONCLUSION

NK cell-associated CRC subtypes can be used to evaluate the tumor characteristics of CRC patients and provide an important reference for CRC patients.

Pangenome characterization and analysis of the NAC gene family reveals genes for Sclerotinia sclerotiorum resistance in sunflower (Helianthus annuus)

BACKGROUND

Sunflower (Helianthus annuus) is one of the most important economic crops in oilseed production worldwide. The different cultivars exhibit variability in their resistance genes. The NAC transcription factor (TF) family plays diverse roles in plant development and stress responses. With the completion of the H. annuus genome sequence, the entire complement of genes coding for NACs has been identified. However, the reference genome of a single individual cannot cover all the genetic information of the species.

RESULTS

Considering only a single reference genome to study gene families will miss many meaningful genes. A pangenome-wide survey and characterization of the NAC genes in sunflower species were conducted. In total, 139 HaNAC genes are identified, of which 114 are core and 25 are variable. Phylogenetic analysis of sunflower NAC proteins categorizes these proteins into 16 subgroups. 138 HaNACs are randomly distributed on 17 chromosomes. SNP-based haplotype analysis shows haplotype diversity of the HaNAC genes in wild accessions is richer than in landraces and modern cultivars. Ten HaNAC genes in the basal stalk rot (BSR) resistance quantitative trait loci (QTL) are found. A total of 26 HaNAC genes are differentially expressed in response to Sclerotinia head rot (SHR). A total of 137 HaNAC genes are annotated in Gene Ontology (GO) and are classified into 24 functional groups. GO functional enrichment analysis reveals that HaNAC genes are involved in various functions of the biological process.

CONCLUSIONS

We identified NAC genes in H. annuus (HaNAC) on a pangenome-wide scale and analyzed S. sclerotiorum resistance-related NACs. This study provided a theoretical basis for further genomic improvement targeting resistance-related NAC genes in sunflowers.

Colorectal cancer subtyping and prognostic model construction based on interleukin-related genes

Members of the interleukin (IL) family are closely linked to cancer development and progression. However, research on the prognosis of colorectal cancer (CRC) related to IL is still lacking. This study investigated new CRC prognostic markers and offered new insights for CRC prognosis and treatment. CRC-related data and IL gene data were collected from public databases. Sample clustering was done with the NMF package to divide samples into different subtypes. Differential, enrichment, survival, and immune analyses were conducted on subtypes. A prognostic model was constructed using regression analysis. Drug sensitivity analysis was performed using GDSC database. Western blot analysis was performed to assess the effect of IL-7 on the JAK/STAT signaling pathway. Flow cytometry was used to examine the impact of IL-7 on CD8+ T cell apoptosis. Two CRC subtypes based on IL-associated genes were obtained. Cluster 1 had a higher survival rate than cluster 2, and they showed differences in some immune levels. The two clusters were mainly enriched in the JAK-STAT signaling pathway, T helper 17 cell differentiation, and the IL-17 signaling pathway. An 11-gene signature was built, and risk score was an independent prognosticator for CRC. The low-risk group showed a higher sensitivity to nine common targeted anticancer drugs. Western blot and flow cytometry results demonstrated that IL-7 could phosphorylate STAT5 and promote survival of CD8+ T cells. In conclusion, this study divided CRC samples into two IL-associated subtypes and obtained an 11-gene signature. In addition, targeted drugs that may improve the prognosis of patients with CRC were identified. These findings are of paramount importance for patient prognosis and CRC treatment.NEW & NOTEWORTHY We identified two clusters with significant survival differences in colorectal cancer (CRC) based on interleukin-related genes, constructed an 11-gene risk score model that can independently predict the prognosis of CRC, and explored some targeted drugs that may improve the prognosis of patients with CRC. The results of this study have important implications for the prognosis and treatment of CRC.

Evaluating cell culture reliability in pediatric brain tumor primary cells through DNA methylation profiling

In vitro models of pediatric brain tumors (pBT) are instrumental for better understanding the mechanisms contributing to oncogenesis and testing new therapies; thus, ideally, they should recapitulate the original tumor. We applied DNA methylation (DNAm) and copy number variation (CNV) profiling to characterize 241 pBT samples, including 155 tumors and 86 pBT-derived cell cultures, considering serum vs serum-free conditions, late vs early passages, and dimensionality (2D vs 3D cultures). We performed a t-SNE classification and identified differentially methylated regions in tumors compared to cell models. Early cell cultures recapitulate the original tumor, but serum media and 2D culturing were demonstrated to significantly contribute to the divergence of DNAm profiles from the parental ones. All divergent cells clustered together acquiring a common deregulated epigenetic signature suggesting a shared selective pressure. We identified a set of hypomethylated genes shared among unfaithful cells converging on response to growth factors and migration pathways, such as signaling cascade activation, tissue organization, and cellular migration. In conclusion, DNAm and CNV are informative tools that should be used to assess the recapitulation of pBT-cells from parental tumors.

T cell-mediated tumor killing sensitivity gene signature-based prognostic score for acute myeloid leukemia

BACKGROUND AND OBJECTIVE

Acute myeloid leukemia (AML) is an aggressive, heterogenous hematopoetic malignancies with poor long-term prognosis. T-cell mediated tumor killing plays a key role in tumor immunity. Here, we explored the prognostic performance and functional significance of a T-cell mediated tumor killing sensitivity gene (GSTTK)-based prognostic score (TTKPI).

METHODS

Publicly available transcriptomic data for AML were obtained from TCGA and NCBI-GEO. GSTTK were identified from the TISIDB database. Signature GSTTK for AML were identified by differential expression analysis, COX proportional hazards and LASSO regression analysis and a comprehensive TTKPI score was constructed. Prognostic performance of the TTKPI was examined using Kaplan-Meier survival analysis, Receiver operating curves, and nomogram analysis. Association of TTKPI with clinical phenotypes, tumor immune cell infiltration patterns, checkpoint expression patterns were analysed. Drug docking was used to identify important candidate drugs based on the TTKPI-component genes.

RESULTS

From 401 differentially expressed GSTTK in AML, 24 genes were identified as signature genes and used to construct the TTKPI score. High-TTKPI risk score predicted worse survival and good prognostic accuracy with AUC values ranging from 75 to 96%. Higher TTKPI scores were associated with older age and cancer stage, which showed improved prognostic performance when combined with TTKPI. High TTKPI was associated with lower naïve CD4 T cell and follicular helper T cell infiltrates and higher M2 macrophages/monocyte infiltration. Distinct patterns of immune checkpoint expression corresponded with TTKPI score groups. Three agents; DB11791 (Capmatinib), DB12886 (GSK-1521498) and DB14773 (Lifirafenib) were identified as candidates for AML.

CONCLUSION

A T-cell mediated killing sensitivity gene-based prognostic score TTKPI showed good accuracy in predicting survival in AML. TTKPI corresponded to functional and immunological features of the tumor microenvironment including checkpoint expression patterns and should be investigated for precision medicine approaches.

Construction of a prognostic model for lung adenocarcinoma based on m6A/m5C/m1A genes

BACKGROUND

Developing a prognostic model for lung adenocarcinoma (LUAD) that utilizes m6A/m5C/m1A genes holds immense importance in providing precise prognosis predictions for individuals.

METHODS

This study mined m6A/m5C/m1A-related differential genes in LUAD based on public databases, identified LUAD tumor subtypes based on these genes, and further built a risk prognostic model grounded in differential genes between subtypes. The immune status between high- and low-risk groups was investigated, and the distribution of feature genes in tumor immune cells was analyzed using single-cell analysis. Based on the expression levels of feature genes, a projection of chemotherapeutic and targeted drugs was made for individuals identified as high-risk. Ultimately, cell experiments were further verified.

RESULTS

The 6-gene risk prognosis model based on differential genes between tumor subtypes had good predictive performance. Individuals classified as low-risk exhibited a higher (P < 0.05) abundance of infiltrating immune cells. Feature genes were mainly distributed in tumor immune cells like CD4+T cells, CD8+T cells, and regulatory T cells. Four drugs with relatively low IC50 values were found in the high-risk group: Elesclomol, Pyrimethamine, Saracatinib, and Temsirolimus. In addition, four drugs with significant positive correlation (P < 0.001) between IC50 values and feature gene expression were found, including Alectinib, Estramustine, Brigatinib, and Elesclomol. The low expression of key gene NTSR1 reduced the IC50 value of irinotecan.

CONCLUSION

Based on the m6A/m5C/m1A-related genes in LUAD, LUAD patients were divided into 2 subtypes, and a m6A/m5C/m1A-related LUAD prognostic model was constructed to provide a reference for the prognosis prediction of LUAD.

Subtyping and prognostic model construction based on vesicle-mediated transport-related genes in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is impacted by various environmental and genetic variables. Dysregulation of vesicle-mediated transport-related genes (VMTRGs) has been observed in many malignancies, but their effect on prognosis in CRC remains unclear.

METHODS

CRC samples were clustered into varying subtypes per differential expression of VMTRGs. R package was utilized to explore differences in survival, immune, and drug sensitivity among different disease subtypes. According to differentially expressed genes (DEGs) between subtypes, regression analysis was employed to build a riskscore model and identify independent prognostic factors. The model was validated through a Gene Expression Omnibus (GEO) dataset. Immune landscape, immunophenoscore (IPS), and Tumor Immune Dysfunction and Exclusion (TIDE) scores for different risk groups were calculated.

RESULTS

Two subtypes of CRC were identified based on VMTRGs, which showed significant differences in survival rates, immune cell infiltration abundance, immune functional activation levels, and immune checkpoint expression levels. Cluster2 exhibited higher sensitivity to anti-tumor drugs such as Nilotinib, Cisplatin, and Oxaliplatin compared to Cluster1. DEGs were mainly enriched in biological processes such as epidermis development, epidermal cell differentiation, and receptor-ligand activity, and signaling pathways like pancreatic secretion. The constructed 13-gene riskscore model demonstrated good predictive ability for CRC patients' prognosis. Furthermore, differences in immune landscape, IPS, and TIDE scores were observed among different risk groups.

CONCLUSION

This study successfully obtained two CRC subtypes with distinct survival statuses and immune levels based on differential expression of VMTRGs. A 13-gene risk model was constructed. The findings had important implications for prognosis and treatment of CRC.

Molecular Characterization and Subtyping of Breast Cancer Cell Lines Provide Novel Insights into Cancer Relevant Genes

Continuous cell lines are important and commonly used in vitro models in breast cancer (BC) research. Selection of the appropriate model cell line is crucial and requires consideration of their molecular characteristics. To characterize BC cell line models in depth, we profiled a panel of 29 authenticated and publicly available BC cell lines by mRNA-sequencing, mutation analysis, and immunoblotting. Gene expression profiles separated BC cell lines in two major clusters that represent basal-like (mainly triple-negative BC) and luminal BC subtypes, respectively. HER2-positive cell lines were located within the luminal cluster. Mutation calling highlighted the frequent aberration of TP53 and BRCA2 in BC cell lines, which, therefore, share relevant characteristics with primary BC. Furthermore, we showed that the data can be used to find novel, potential oncogenic fusion transcripts, e.g., FGFR2::CRYBG1 and RTN4IP1::CRYBG1 in cell line MFM-223, and to elucidate the regulatory circuit of IRX genes and KLF15 as novel candidate tumor suppressor genes in BC. Our data indicated that KLF15 was activated by IRX1 and inhibited by IRX3. Moreover, KLF15 inhibited IRX1 in cell line HCC-1599. Each BC cell line carries unique molecular features. Therefore, the molecular characteristics of BC cell lines described here might serve as a valuable resource to improve the selection of appropriate models for BC research.

Prediction of prognostic and immune therapy response in lung adenocarcinoma based on MHC-I-related genes

OBJECTIVES

The study investigated the prognostic and immune predictive potential of major histocompatibility complex class I (MHC-I) in lung adenocarcinoma (LUAD).

MATERIALS AND METHODS

With The Cancer Genome Atlas (TCGA)-LUAD and Gene Expression Omnibus datasets (GSE26939, GSE72094) as the training and validation sets, respectively, we used Cox regression analysis to construct a prognostic model, and verified independence of riskscore. The predictive capacity of the model was assessed in both sets using the receiver operating characteristic curve and Kaplan-Meier survival curves. Immune analysis was performed by using ssGSEA. Additionally, immune checkpoint blockade therapy was assessed by using immunophenoscore, Tumor Immune Dysfunction and Exclusion score. Based on the cMAP database, effective small molecule compounds were predicted.

RESULTS

A prognostic model was established based on 8 MHC-I-related genes, and the predictive capacity of the model was accurate. Immune analysis results revealed that patients classified as high-risk had lower levels of immune cell infiltration and impaired immune function. The low-risk group possessed a better response to immune checkpoint blockade therapy. Theobromine and pravastatin were identified as having great potential in improving the prognosis of LUAD.

CONCLUSION

Overall, the study revealed MHC-I-related molecular prognostic biomarkers as robust indicators for LUAD prognosis and immune therapy response.

A Lactic Acid Metabolism-Related Gene Signature for Predicting Clinical Outcome and Tumor Microenvironmental Status in Patients with Hepatocellular Carcinoma

This study aims to build a prognostic model based on lactic acid metabolism-related genes (LMRGs) to predict survival outcomes and tumor microenvironment status of Hepatocellular carcinoma (HCC) patients. The model was used to calculate riskscores of clinical samples. Survival analysis and Cox regression analysis were conducted to verify the independence and reliability of the riskscore to determine its clinical significance in prognosis evaluation of HCC. Additionally, we conducted a comprehensive analysis of tumor mutation burden (TMB), immune cell infiltration, and gene set molecular function in the high- and low-risk groups. We obtained 134 LMRGs mainly involved in cellular calcium homeostasis and calcium signaling pathways. The LMRGs in the risk assessment model included PFKFB4, SLC16A3, ADRA2B, SLC22A1, QRFPR, and PROK1. This study discovered much shorter overall survival and median survival time of patients with higher riskscores when compared to those with lower riskscores. It was indicated that for independent prediction of patients' prognosis, the riskscore had a significant clinical value. A remarkable difference was also found regarding TMB between the two groups. Finally, cell experiments demonstrated that the knockout of PFKFB4 and SLC16A3 genes suppressed lactate. Our research demonstrated that the riskscore, established based on LMRGs, is a promising biomarker.

Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity

POLE driver mutations in the exonuclease domain (ExoD driver) are prevalent in several cancers, including colorectal cancer and endometrial cancer, leading to dramatically ultra-high tumor mutation burden (TMB). To understand whether POLE mutations that are not classified as drivers (POLE Variant) contribute to mutagenesis, we assessed TMB in 447 POLE-mutated colorectal cancers, endometrial cancers, and ovarian cancers classified as TMB-high ≥10 mutations/Mb (mut/Mb) or TMB-low <10 mut/Mb. TMB was significantly highest in tumors with "POLE ExoD driver plus POLE Variant" (colorectal cancer and endometrial cancer, P < 0.001; ovarian cancer, P < 0.05). TMB increased with additional POLE variants (P < 0.001), but plateaued at 2, suggesting an association between the presence of these variants and TMB. Integrated analysis of AlphaFold2 POLE models and quantitative stability estimates predicted the impact of multiple POLE variants on POLE functionality. The prevalence of immunogenic neoepitopes was notably higher in the "POLE ExoD driver plus POLE Variant" tumors. Overall, this study reveals a novel correlation between POLE variants in POLE ExoD-driven tumors, and ultra-high TMB. Currently, only select pathogenic ExoD mutations with a reliable association with ultra-high TMB inform clinical practice. Thus, these findings are hypothesis-generating, require functional validation, and could potentially inform tumor classification, treatment responses, and clinical outcomes.

SIGNIFICANCE

Somatic POLE ExoD driver mutations cause proofreading deficiency that induces high TMB. This study suggests a novel modifier role for POLE variants in POLE ExoD-driven tumors, associated with ultra-high TMB. These data, in addition to future functional studies, may inform tumor classification, therapeutic response, and patient outcomes.

A glycosylation-related gene signature predicts prognosis, immune microenvironment infiltration, and drug sensitivity in glioma

Glioma represents the most common primary cancer of the central nervous system in adults. Glycosylation is a prevalent post-translational modification that occurs in eukaryotic cells, leading to a wide array of modifications on proteins. We obtained the clinical information, bulk RNA-seq data, and single-cell RNA sequencing (scRNA-seq) from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), Gene Expression Omnibus (GEO), and Repository of Molecular Brain Neoplasia Data (Rembrandt) databases. RNA sequencing data for normal brain tissues were accessed from the Genotype-Tissue Expression (GTEx) database. Then, the glycosylation genes that were differentially expressed were identified and further subjected to variable selection using a least absolute shrinkage and selection operator (LASSO)-regularized Cox model. We further conducted enrichment analysis, qPCR, nomogram, and single-cell transcriptome to detect the glycosylation signature. Drug sensitivity analysis was also conducted. A five-gene glycosylation signature (CHPF2, PYGL, GALNT13, EXT2, and COLGALT2) classified patients into low- or high-risk groups. Survival analysis, qPCR, ROC curves, and stratified analysis revealed worse outcomes in the high-risk group. Furthermore, GSEA and immune infiltration analysis indicated that the glycosylation signature has the potential to predict the immune response in glioma. In addition, four drugs (crizotinib, lapatinib, nilotinib, and topotecan) showed different responses between the two risk groups. Glioma cells had been classified into seven lines based on single-cell expression profiles. The five-gene glycosylation signature can accurately predict the prognosis of glioma and may offer additional guidance for immunotherapy.

Pituitary neuroendocrine tumors with PIT1/SF1 co-expression show distinct clinicopathological and molecular features

Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed "plurihormonal". Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as "plurihormonal", and calls for a refinement of the WHO classification. We propose the term "somatogonadotroph PitNET".

Evolutionary mode and timing of dissemination of high-grade serous carcinomas

Dissemination within the peritoneal cavity is a main determinant of poor patient outcomes from high-grade serous carcinomas (HGSCs). The dissemination process is poorly understood from a cancer evolutionary perspective. We reconstructed the evolutionary trajectories across a median of 5 tumor sites and regions from each of 23 patients based on deep whole-exome sequencing. Polyclonal cancer origin was detected in 1 patient. Ovarian tumors had more complex subclonal architectures than other intraperitoneal tumors in each patient, which indicated that tumors developed earlier in the ovaries. Three common modes of dissemination were identified, including monoclonal or polyclonal dissemination of monophyletic (linear) or polyphyletic (branched) subclones. Mutation profiles of initial or disseminated clones varied greatly among cancers, but recurrent mutations were found in 7 cancer-critical genes, including TP53, BRCA1, BRCA2, and DNMT3A, and in the PI3K/AKT1 pathway. Disseminated clones developed late in the evolutionary trajectory models of most cancers, in particular in cancers with DNA damage repair deficiency. Polyclonal dissemination was predicted to occur predominantly as a single and rapid wave, but chemotherapy exposure was associated with higher genomic diversity of disseminated clones. In conclusion, we described three common evolutionary dissemination modes across HGSCs and proposed factors associated with dissemination diversity.

Malignant peripheral nerve sheath tumor (MPNST) and MPNST-like entities are defined by a specific DNA methylation profile in pediatric and juvenile population

BACKGROUND

Malignant peripheral nerve sheath tumors (MPNSTs) account for 3-10% of pediatric sarcomas, 50% of which occur in neurofibromatosis type 1 (NF1). Sporadic MPNSTs diagnosis may be challenging due to the absence of specific markers, apart from immunohistochemical H3K27me3 loss. DNA methylation (DNAm) profiling is a useful tool for brain and mesenchymal neoplasms categorization, and MPNSTs exhibit a specific DNAm signature. An MPNST-like group has recently been recognized, including pediatric tumors with retained H3K27me3 mark and clinical/histological features not yet well explored. This study aims to characterize the DNAm profile of pediatric/juvenile MPNSTs/MPNST-like entities and its diagnostic/prognostic relevance.

RESULTS

We studied 42 tumors from two groups. Group 1 included 32 tumors histologically diagnosed as atypical neurofibroma (ANF) (N = 5) or MPNST (N = 27); group 2 comprised 10 tumors classified as MPNST-like according to Heidelberg sarcoma classifier. We performed further immunohistochemical and molecular tests to reach an integrated diagnosis. In group 1, DNAm profiling was inconclusive for ANF; while, it confirmed the original diagnosis in 12/27 MPNSTs, all occurring in NF1 patients. Five/27 MPNSTs were classified as MPNST-like: Integrated diagnosis confirmed MPNST identity for 3 cases; while, the immunophenotype supported the change to high-grade undifferentiated spindle cell sarcoma in 2 samples. The remaining 10/27 MPNSTs variably classified as schwannoma, osteosarcoma, BCOR-altered sarcoma, rhabdomyosarcoma (RMS)-MYOD1 mutant, RMS-like, and embryonal RMS or did not match with any defined entity. Molecular analysis and histologic review confirmed the diagnoses of BCOR, RMS-MYOD1 mutant, DICER1-syndrome and ERMS. Group 2 samples included 5 high-grade undifferentiated sarcomas/MPNSTs and 5 low-grade mesenchymal neoplasms. Two high-grade and 4 low-grade lesions harbored tyrosine kinase (TRK) gene fusions. By HDBSCAN clustering analysis of the whole cohort we identified two clusters mainly distinguished by H3K27me3 epigenetic signature. Exploring the copy number variation, high-grade tumors showed frequent chromosomal aberrations and CDKN2A/B loss significantly impacted on survival in the MPNSTs cohort.

CONCLUSION

DNAm profiling is a useful tool in diagnostic work-up of MPNSTs. Its application in a retrospective series collected during pre-molecular era contributed to classify morphologic mimics. The methylation group MPNST-like is a 'hybrid' category in pediatrics including high-grade and low-grade tumors mainly characterized by TRK alterations.

Construction of a Liver Cancer Prognostic Model Based on Interferon-Gamma-Related Genes for Revealing the Immune Landscape

Inferferon-gamma (LFN-γ) exerts anti-tumor effects, but there is currently no reliable and comprehensive study on prognostic function of IFN-γ-related genes in liver cancer. In this study, IFN-γ-related differentially expressed genes (DEGs) in liver cancer were identified through GO/KEGG databases and open-access literature. Based on these genes, individuals with liver cancer were clustered. A prognostic model was built based on the intersection genes between differential genes in clusters and in liver cancer. Then, model predictive performance was analyzed and validated in GEO dataset. Regression analysis was fulfilled on the model, and a nomogram was utilized to evaluate model ability as an independent prognostic factor and its clinical application value. An immune-related analysis was conducted on both the H- and L-groups, with an additional investigation into link of model genes to drug sensitivity. Significant differential expression of IFN-γ-related genes was observed between the liver cancer and control groups. Subsequently, individuals with liver cancer were classified into two subtypes based on these genes, which displayed a notable difference in survival between the two subtypes. A 10-gene liver cancer prognostic model was constructed, with good prognostic performance and was an independent prognosticator for patient analysis. L-group patients possessed higher immune infiltration levels, immune checkpoint expression levels, and immunophenoscore, as well as lower TIDE scores. Drugs that had high correlations with the feature genes included SPANXB1: PF-04217903, SGX-523, MMP1: PF-04217903, DUSP13: Imatinib, TFF1: KHK-Indazole, and Fulvestrant. We built a 10-gene liver cancer prognostic model. It was found that L-group patients were more suitable for immunotherapy. This study provided valuable information on the prognosis of liver cancer.

MiR-301b-3p can be used as a Potential Marker for the Diagnosis of Lung Adenocarcinoma

BACKGROUND

The involvement of aberrantly expressed miR-301b-3p has been discovered in diverse human tumors. Our study was primarily centered around the role of miR-301b-3p in diagnosing lung adenocarcinoma (LUAD).

METHOD

We used the TCGA database to download the TCGA-LUAD dataset and selected miR- 301b-3p as the object of our study by differential expression analysis of miRNAs combined with previous studies. The LUAD diagnostic model was constructed utilizing machine learning based on miR-301b-3p expression. The predictive performance of the diagnostic model was found to be excellent by ROC curves combined with the clinical information of the dataset samples. GSEA, GO, and KEGG enrichment analyses demonstrated that miR-301b-3p may mediate the cell cycle by regulating the expression of hormones. Subsequently, combined with tumor immunity and mutation analysis, it was found that patients in the low-expression group had better immune infiltration, indicating that their response rate to immunotherapy may be relatively high. Finally, a mouse xenograft model was constructed to verify how miR-301b-3p affected LUAD progression in mice.

RESULT

The results illustrated that overexpressed miR-301b-3p could cause faster tumor growth in mice. On the contrary, the growth of LUAD could be impeded by the downregulated miR-301b-3p expression. It was suggested that miR-301b-3p had a crucial part in LUAD progression.

CONCLUSION

Overall, the diagnostic performance of the LUAD diagnostic model constructed based on miR-301b-3p is great, and the model can be used as a potential diagnostic marker for LUAD to provide new ideas for clinical diagnosis.

Classification and immunotherapy assessment of lung adenocarcinoma based on coagulation-related genes

Introduction: This study on lung adenocarcinoma (LUAD), a common lung cancer subtype with high mortality. Aims: This study focuses on how tumor cell interactions affect immunotherapy responsiveness. Methods: Using public databases, we used non-negative matrix factorization clustering method, ssGSEA, CIBERSORT algorithm, immunophenotype score, survival analysis, protein-protein interaction network method to analyze gene expression data and coagulation-related genes. Results: We divided LUAD patients into three coagulation-related subgroups with varying immune characteristics and survival rates. A cluster of three patients, having the highest immune infiltration and survival rate, also showed the most potential for immunotherapy. We identified five key genes influencing patient survival using a protein-protein interaction network. Conclusion: This research offers valuable insights for forecasting prognosis and immunotherapy responsiveness in LUAD patients, helping to inform clinical treatment strategies.

Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters

Copy number alterations (CNAs) are frequently observed in early-stage prostate cancer and are associated with disease recurrence and tumor aggressiveness. Cost-effective assessment of CNAs could enhance clinical utility of CNAs. Here, we combined the cost-effectiveness of low-pass (low coverage) whole genome sequencing (LPWGS) and the routine availability of formalin-fixed paraffin-embedded (FFPE) tumor tissue for assessing CNAs in a cohort of 187 men with early-stage localised prostate cancer. We detected well known CNAs in 8p, 8q, 13q and 16q and recurrent gains of the oncogene MYC and losses of the tumor suppressor genes NKX3-1, PTEN and RB1, indicating assay reliability. The estimated burden of CNAs was significantly associated with Gleason score, pathological T stage, surgical margin status and biochemical recurrence. Further, genomic losses or gains in specific chromosomal arms were significantly associated with worse BCR-free survival. Copy number signatures extracted from the LPWGS data showed potential for risk stratifying patients, where signatures S1 and S2 showed significant association to worse BCR-free survival compared to S3. Our study provides clinical validation of the associations between CNAs and tumor aggressiveness in an independent and representative RP cohort, while demonstrating the feasibility of performing LPWGS of FFPE tumor tissue for cost-effective assessment of CNAs.

Identification of prognostic biomarkers of breast cancer based on the immune-related gene module

Breast cancer (BC) is highly malignant and its mortality rate remains high. The development of immunotherapy has gradually improved the prognosis and survival rate of patients. Therefore, identifying molecular markers concerned with BC immunity is of great importance for the treatment of this disease. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) was utilized as the training set while the BC expression dataset from the gene expression omnibus database was taken as the validation set here. Weighted gene co-expression network analysis combined with Pearson analysis and Tumor immune estimation resource (TIMER) was used to obtain immune cell-related hub gene module. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed on this module. Then, receiver operating characteristic curves combining Kaplan-Meier was used to evaluate the effectiveness of the model. Feature genes were screened and the independence of risk score was evaluated by univariate and multivariate Cox analyses. Differences in immune characteristics were analyzed via single-sample gene set enrichment analysis and CIBERSORT, and differences in gene mutation frequency were assessed via GenVisR analysis. Finally, the expression levels of prognostic feature genes in BC cells were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). In this study, cell immune-related gene modules in TCGA-BRCA were successfully excavated, and a five-gene (TNFRSF14, NFKBIA, DLG3, IRF2, and CYP27A1) prognostic model was established. The prognostic model could effectively forecast the prognosis and survival rate of BC patients. The result showed that human leukocyte antigen-related proteins and macrophage M2 scores were remarkably highly expressed in the high-risk group, whereas CD8+ T cells, natural killer cells, M1, and other anti-tumor cells were lowly expressed. The model could be used as an independent prognostic factor to predict the prognosis of BC patients. The results of qRT-PCR validation were consistent with the results in the database, that is, except DLG3, the other four feature genes were lowly expressed in BC. The five-gene model established in this study can predict the prognostic and immune mode of BC patients effectively, which is anticipated to become a feasible molecular target for BC therapy.

Prognostic characteristics of T-cell mediated cell killing-related genes in lung adenocarcinoma

Constituted by various heterogeneous cells, the tumor microenvironment (TME) is capable of promoting tumor proliferation, invasion, and metastasis through extensive crosstalk. The pivotal factor influencing the survival time of patients and their response to immunotherapy lies in the intratumoral immune environment. We obtained 112 differential genes related to T cell-mediated tumor killing in LUAD by employing bioinformatics analysis on the basis of the TCGA and TISIDB databases. Then the 6-gene prognostic risk score model (CA9, OIP5, TIMP1, SEC11C, FURIN, and TLR10) was constructed by conducting univariate LASSO as well as multivariate Cox regression analyses. The median risk score was taken as the threshold to classify the samples into two groups. Survival analysis revealed that the low-risk group exhibited a more favorable prognosis. Subsequently, the Cox regression analysis combined with clinical information (age, gender, and pathological stage) and the risk score of LUAD patients demonstrated the potential of this model as an independent prognostic factor. The nomogram established based on clinical information and a risk score in combination with the calibration curve indicated that this model had good predictive ability. Notable enrichment of the differential genes from the high- and low-risk groups was discovered in immune-associated processes or pathways, as shown by the GO and KEGG enrichment analyses. The combined use of single-sample gene enrichment analysis (ssGSEA) and immunophenoscore (IPS) demonstrated heightened immune infiltration and IPS scores in the low-risk group, indicating that immunotherapy was likely to show good efficacy in patients from this group. To sum up, the prognostic model of LUAD constructed based on T-cell-mediated cell killing-related genes was not only capable of screening the prognosis of LUAD patients but was also used for screening those LUAD patients with high sensitivity to immunotherapy. Our study offered novel insights into the clinical treatment and prognostic prediction of LUAD patients.

Recognition and combination of multiple cell-death features showed good predictive value in lung adenocarcinoma

BACKGROUND

Cell death is a key regulatory process in organisms and its study has become increasingly important in the field of cancer. While prior research has primarily centered on the individual pathways of cell death in cancer, there has been a lack of comprehensive investigation into the synergistic effects of multiple cell death pathways.

METHODS

Genes related to autophagy, apoptosis, necroptosis, pyroptosis, and cuproptosis was selected, and patients' data was collected from The Cancer Genome Atlas (TCGA)project. Cell death features were identified using principal component analysis and combined to create a composite score. A scalable prediction model was then created using LASSO regression after a thorough assessment of the composite scores. The model was subsequently validated across multiple external datasets to establish its robustness and reliability.

RESULTS

The cell death features effectively represented the gene expression patterns in the samples. The composite score well predicted prognosis, clinical stage, mutation, tumor microenvironment, and immunotherapy effectiveness. The model built on composite scores accurately predicted prognosis and immunotherapy effectiveness across multiple datasets. GJB2 was identified as a potential biomarker.

CONCLUSION

Models based on multiple cell death pathways have significant predictive power for prognosis and immunotherapy effectiveness in lung adenocarcinoma. This highlights the synergistic role of multiple cell death pathways in cancer development and offers a new perspective for cancer research.