Cancer Genome Research Articles

Development and validation of a prognostic model for colon cancer based on mitotic gene signatures and immune microenvironment analysis

BackgroundMitotic processes play a pivotal role in tumor progression and immune responses. However, the correlation between mitosis-related genes, clinical outcomes, and the tumor microenvironment (TME) in colon cancer remains unclear. This study aims to develop a prognostic and therapeutic significance model for colon cancer based on mitosis-related genes.MethodsRNA expression profiles and clinical data of 453 colon cancer patients were downloaded from The Cancer Genome Atlas (TCGA). Mitosis-related genes were selected from the MsigDb database. The gene model was constructed using differential analysis, univariate and multivariate Cox regression, and Lasso regression analyses. The predictive model was validated using data from the GSE17536, GSE17537, and GSE39582 datasets. Predictive accuracy was evaluated via Receiver Operating Characteristic (ROC) curves, while nomograms were developed by integrating clinical and pathological features. Gene set enrichment analysis explored biological processes and pathways linked to the model. TME was assessed using ESTIMATE, and the proportion and function of immune cells were analyzed through CIBERSORT. Drug sensitivity analysis was conducted using the CTRP database.ResultsA predictive model based on 17 mitosis-related genes (KIFC1, CCNF, EME1, CDC25C, ORC1, CCNJL, ANKRD53, MEIS2, FZD3, TPD52L1, MAPK3, CDKN2A, EDN3, NPM2, PSRC1, INHBA, BIRC5) was created. The model exhibited robust predictive performance across both training and validation cohorts. Nomograms for predicting 3-, 5-, and 7-year survival rates in colon cancer (COAD) patients were generated. The model's correlation with immune cell infiltration and function was highlighted.ConclusionThe mitosis-related gene model serves as a valuable indicator for predicting survival outcomes in colon cancer patients.

Exploring the role of ADAMTSL2 across multiple cancer types: A pan-cancer analysis and validated in colorectal cancer

BackgroundRecent studies have established a correlation between ADAMTSL2 (ADAMTS-like 2) and the development of various cancers. This study aims to conduct a comprehensive pan-cancer analysis in 37 cancer types and investigate its potential role in colon and rectal adenocarcinoma (COADREAD).MethodPan-cancer and mutation data were sourced from The Cancer Genome Atlas (TCGA) database and analyzed using Sangerbox analysis platform. We explored the expression patterns and prognostic implications of ADAMTSL2, and investigated its relationships with tumor heterogeneity, stemness, immune checkpoint genes, immune cell infiltration, RNA modifications, and mutational profiles across different cancers. Additionally, with Ethics Committee approval, we conducted immunohistochemical (IHC) analysis on 120 COADEAD samples to evaluate ADAMTSL2 expression and its association with clinicopathological parameters.ResultsADAMTSL2 expression was positively correlated with the hazard ratio of OS, DSS, DFI and PFI for ESCA and COADREAD. A negative correlation was observed between ADAMTSL2 expression and NEO levels in COAD. Gene alterations in ADAMTSL2 were observed, with a mutation frequency of 5.0% in COAD. There is a significant correlation between ADAMTSL2 expression and immune cell infiltration in a variety of cancers. The expression level of ADAMTSL2 protein was associated with T stage, N stage, M stage (p < 0.05). Kaplan‒Meier survival curves demonstrated that the high ADAMTSL2 group had a shorter OS time (p = 0.047) and progression free survival time (p = 0.026) than the low ADAMTSL2 group.ConclusionIn summary, we conducted a comprehensive pan-cancer analysis of ADAMTSL2 and we demonstrated that ADAMTSL2 may serve as a novel prognostic biomarker and immunotherapy target in COADREAD.

Cancer-Associated Fibroblast Subtypes Reveal Distinct Gene Signatures in the Tumor Immune Microenvironment of Vestibular Schwannoma.

Cancer-associated fibroblast (CAF) composition within the same organ varies across different cancer subtypes. Distinct CAF subtypes exhibit unique features due to interactions with immune cells and the tumor microenvironment. However, data on CAF subtypes in individuals with vestibular schwannoma (VS) are lacking. Therefore, we aimed to distinguish CAF subtypes at the single-cell level, investigate how stem-like CAF characteristics influence the tumor immune microenvironment, and identify CAF subtype-specific metabolic reprogramming pathways that contribute to tumor development. Data were analyzed from three patients with VS, encompassing 33,081 single cells, one bulk transcriptome cohort, and The Cancer Genome Atlas Pan-Cancer database (RNA sequencing and clinical data). Our findings revealed that antigen-presenting CAFs are linked to substantially heightened immune activity, supported by metabolic reprogramming, which differs from tumorigenesis. High expression of the stem-like CAF gene signature correlated with poor prognosis in low-grade gliomas within the pan-cancer database. This is the first study to classify CAF subtypes in VS patients and identify a therapeutic vulnerability biomarker by developing a stem-like CAF gene signature. Personalized treatments tailored to individual patients show promise in advancing precision medicine.

Identification and Verification of Key Genes in Colorectal Cancer Liver Metastases Through Analysis of Single-Cell Sequencing Data and TCGA Data

BackgroundColorectal cancer (CRC) is highly prevalent worldwide, with more patients experiencing colorectal cancer liver metastases (CRLM). This study aimed to identify key genes in CRLM through single-cell sequencing data reanalysis and experimental validation.MethodsThe study analyzed single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The Cancer Genome Atlas (TCGA) data enabled bulk-RNA expression and survival prognosis analysis. Real-time polymerase chain reaction (qPCR) detected mRNA expression, whereas Western blot determined protein levels. Cell function experiments assessed SPARC’s impact on CRC cell behavior.ResultsCluster analysis showed 23 classes among 17 CRLM samples, representing six cell types. A GO and KEGG analysis identified interleukin-1 beta (IL1B), CD2 molecule (CD2), and C-X-C motif chemokine ligand 8 (CXCL8) as significant prognostic factors in CRC. Secreted protein acidic and cysteine rich (SPARC) was one of the top differentially expressed genes (DEGs) in tissue stem cells, confirmed in primary and metastatic lesions. Metastatic lesions showed higher expression of SPARC and CRC stem cell marker leucine-rich repeat containing G protein-coupled receptor 5 (LGR5), which was significantly correlated positively with LGR5 expression. Knockdown of SPARC reduced CRC cell sphere- and colony-formation, invasion, and migration abilities. Overexpression of SPARC significantly increased the malignancy of CRC cells.ConclusionsSeveral key genes were identified in the process of CRLM. In CRLM samples and those corresponding to CRC stem cells, SPARC was significantly upregulated. In the therapy of CRLM, SPARC might be a potential target.

Pan-cancer analysis of TP53 mutations and their association with liver cancer and aristolochic acids

Liver cancer is a major global health concern, as its incidence continues to rise in numerous countries, making it a leading cause of cancer-related deaths. The TP53 gene, which encodes the p53 tumor suppressor protein, plays a crucial role in regulating cell growth and division. Mutations in TP53 have been implicated in increased risk for liver cancer development. In this study, we aim to conduct a pan-cancer analysis to further investigate the potential role of TP53 mutations in various cancer types and their relationship with liver cancer. Additionally, we will explore the interplay between TP53 gene mutations, liver cancer, and exposure to Aristolochic acids (AAs). To achieve these goals, we will utilize data from The Cancer Genome Atlas (TCGA) project and the Gene Expression Omnibus (GEO) databases, enabling a comprehensive analysis of TP53 in the context of multiple cancer types.

The Prospective role of lapatinib as an adjuvant therapy in prevalent cancers: Insights from in silico analysis targeting EGFR and HER2

IntroductionVarious pieces of evidence suggest an elevation in the levels of EGFR and HER2 in different cancers leading to the proliferation, invasion, and metastasis of cancer cells. In this study, we conducted a comprehensive investigation into the expression alterations of these two receptors in various cancers using in silico data. In addition, we investigated the therapeutic potential of lapatinib as an inhibitor of these receptors in various cancer types. MethodsRNAseq data for prevalent cancers were downloaded from The Cancer Genome Atlas (TCGA). After initial preprocessing, expression changes of HER2, EGFR, and candidate genes—identified based on their association with EGFR and HER2 signaling pathways—were examined. Human protein atlas data were utilized to assess the protein expression of HER2 and EGFR. GSE129254 was employed to identify molecular pathways and candidate genes associated with lapatinib. The protein-protein interaction network was used to identify lapatinib-influenced hub genes. Clinical data for common cancers were used to investigate the correlation between the expression of candidate genes and patients' mortality rates by Cox regression test. ResultsThe findings clearly indicated a significant increase in the expression levels of HER2 and EGFR in cancers such as kidney, lung, breast, bladder, pancreas, head and neck, stomach, and endometrial, both at the mRNA and protein levels (p-value <0.01). Additionally, more than 30 % of samples in some cancers showed a twofold increase in HER2 or EGFR expression. The analysis of GSE129254 data revealed that lapatinib reduces the expression of numerous genes associated with cell proliferation. METTL1, LYAR, LTV1, CCND1, NOP2, and DDX21 were identified as hub genes related to the effect of lapatinib. Our results demonstrated that many hub genes exhibited elevated expression in candidate cancers, and the upregulation of some of them was correlated with poor prognosis. ConclusionOur results indicate an upregulation in the expression levels of HER2 and EGFR in certain common cancers, suggesting that lapatinib, in addition to breast cancer, could be considered for the treatment of these cancers. Furthermore, we demonstrated that some genes with increased expression in prevalent cancers and associated with poor prognosis have the potential to be modulated by lapatinib.

Integrative analysis of multiple cell death model for precise prognosis and drug response prediction in gastric cancer.

Gastric cancer (GC) is a common upper gastrointestinal tumor. However, the evaluation of prognosis and treatment response in patients with gastric cancer remains a challenge. Programmed cell death (PCD) is one of the important terminal paths for the cells of metazoans, and is involved in a variety of biological events that include morphogenesis, maintenance of tissue homeostasis, and elimination of harmful cells. The objective of this project is to investigate the predictive significance of cell death pathways and create prognostic signatures associated to cell death, with the purpose of forecasting prognosis and providing guidance for the treatment of gastric cancer. Gene transcription profiles and corresponding clinical data of gastric cancer patients were collected from The Cancer Genome Atlas (TCGA-STAD, n = 448) and the Gene Expression Comprehensive Database (GSE84437, n = 483). Thirteen types of cell death-related genes, including apoptosis, necroptosis, pyroptosis, ferroptosis, autophagy, cuprotosis, parthanatos, entotic cell death, netotic cell death, lysosome-dependent cell death, alkaliptosis, oxeiptosis, and disulfidptosis, were analysed. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Patients were categorized into high and low-risk groups based on the median risk score for survival difference analysis. Cell death-related genes associated with prognosis were identified in the TCGA-STAD training cohort using Lasso-Cox regression to generate a risk score. Additionally, the response to immunotherapy in the high-risk and low-risk groups was calculated using the oncoPredict algorithm. Futhermore, the model genes were validated in the GEO validation set. A total of 324 differential programmed cell death (PCD)-related genes were identified, and 65 were selected through single-factor Cox analysis. Six PCD-related genes were ultimately identified by Lasso regression to construct a prognostic risk score model. The log-rank test revealed that patients in the high-risk group had inferior survival time compared with those in the low-risk group. The area under the ROC curve (AUC) for the training group at years 1, 3, and 5 were 0.684, 0.713, 0.743, respectively, while the AUC for the validation cohort at years 1, 3, and 5 were 0.695, 0.704, and 0.707, respectively. Unsupervised clustering identified potential subtypes included in the model, and a survival difference was also observed between the two subgroups. Multifactor Cox results, combined with clinical information, demonstrated that the prognostic risk score can serve as an independent prognostic factor, irrespective of other clinical features. By comprehensively analyzing multiple cell death patterns, we have established a novel model that accurately forecasts the clinical prognosis and drug sensitivity of gastric cancer. It was found that all 12 representative drugs may not be suitable for patients in high-risk groups.

Neutrophil chemotaxis score and chemotaxis-related genes have the potential for clinical application to prognosticate the survival of patients with tumours

As frontline cells, the precise recruitment of neutrophils is crucial for resolving inflammation and maintaining the homeostasis of the organism. Increasing evidence suggests the pivotal role of neutrophil chemotaxis in cancer progression and metastasis. Here, we collected clinical data and peripheral blood samples from patients with tumours to examine the alterations in the neutrophil quantity and chemotactic function using the Cell Chemotaxis Analysis Platform (CCAP). Transcriptome sequencing data of pan-cancer were obtained from The Cancer Genome Atlas (TCGA). Using the least absolute shrinkage and selection operator (LASSO) Cox regression model, we selected a total of 29 genes from 155 neutrophil- and chemotaxis-related genes to construct the ChemoScore model. Meanwhile, nomogram-based comprehensive model was established for clinical application. Furthermore, immunofluorescence (IF) staining was employed to assess the relationship between the neutrophils infiltrating and the survival outcomes of tumours. In this observational study, the chemotactic function of neutrophils was notably diminished in patients. The establishment and validation of ChemoScore suggested neutrophil chemotaxis to be a risk factor in most tumours, whereby higher scores were associated with poorer survival outcomes and were correlated with various immune cells and malignant biological processes. Moreover, IF staining of tumour tissue substantiated the adverse correlation between neutrophil infiltration and the survival of patients with lung adenocarcinoma (P = 0.0002) and colon adenocarcinoma (P = 0.0472). Taken together, patients with tumours demonstrated a decrease in chemotactic function. ChemoScore potentially prognosticates the survival of patients with tumours. Neutrophil chemotaxis provides novel directions and theoretical foundations for anti-tumour treatment.

The mutated in colorectal cancer (MCC) gene can serve as a potential biomarker of glioblastoma.

The mutated in colorectal cancer (MCC) gene was initially identified as a candidate tumor suppressor gene in colorectal cancer, acting as a negative regulator of cell cycle progression. However, its functional roles in brain tumors, particularly glioblastoma, remain largely unexplored. This study reveals a significant association between MCC status and glioblastoma. We explored MCC expression in the glioblastoma database, patient samples, and cell lines. We investigated the proliferation and migration of the cell lines in MCC gene knockdown using small interfering RNA. In vitro analyses revealed elevated protein and mRNA levels of MCC in several glioblastoma cell lines (U118MG and T98G). Silencing MCC expression via siRNA-mediated knockdown resulted in increased proliferation and migration of these cell lines. Supporting these findings, analyses of The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases confirmed higher MCC expression in glioblastoma tumors than in normal brain tissue. Importantly, we observed that high MCC expression was associated with poor prognosis in glioblastoma patients, highlighting its potential role in disease progression. Additionally, this study identifies a nuclear localization of MCC in the glioblastoma cell line. These findings indicate that MCC expression is significantly upregulated in glioblastoma and may play a role in its pathophysiology, warranting further investigation.

Randomized control trial comparing genetic counseling service delivery models in an underserved population.

This randomized controlled trial compares outcomes of telephone versus in-person genetic counseling service models in underserved, bilingual patient populations referred for cancer genetic counseling. Between 2022 and 2023, a two-arm (telephone vs. in-person genetic counseling) prospective, randomized controlled study with 201 participants was conducted at two county hospital cancer genetics clinics. Primary outcomes included comparison of pre- and post-genetic counseling genetics knowledge (Multi-dimensional Model of Informed Choice, MMIC), genetic counseling visit satisfaction (Genetic Counseling Satisfaction Scale, GCSS), and genetic counseling visit completion rates. Secondary outcomes included comparison of genetic testing attitudes and informed choice (MMIC), genetic counseling-specific empowerment (Genomic Outcomes Scale, GOS), and genetic testing completion and cancellation/failure rates, using linear regression models (significance ≤0.05). There were no statistically significant differences between arms in pre/post-genetic counseling MMIC knowledge and attitude, GOS or GCSS scores or genetic counseling completion. While more participants in the telephone versus in-person arm made an informed choice about testing (52.5% v. 39.0%, p = 0.0552), test completion was lower (74% v. 100%, p < 0.05) for this group. Genetic counseling completion rates and MMICknowledge and attitude, GOS, and GCSS scores suggest telephone genetic counseling is comparable to in-person genetic counseling for underserved populations. Higher informed choice scores and significantly lower testing completion rates for telephone visits require further study.

Unraveling the mechanisms of RECQL4-mediated cervical cancer progression through the PI3K/AKT pathway

BackgroundRECQL4 is a member of the DNA helicase family and is critical for DNA replication, DNA damage repair, and tumor progression. However, its specific role in cervical cancer remains uncertain. MethodsIn this study, we aimed to investigate the impact of RECQL4 on cervical cancer prognosis using clinical specimens from The Cancer Genome Atlas. We evaluated the malignant effects of RECQL4 through various experimental assays including cell Cell Counting Kit-8, EdU, colony formation, cell cycle analysis, cell apoptosis, scratch, and Transwell assays. We explored the mechanisms of RECQL4-regulated malignancy using analyses of bioinformatics, RNA sequencing data, polymerase chain reaction (PCR), western blotting, and cell immunofluorescence experiments. Furthermore, we validated the effects of RECQL4 knockdown on tumor growth using subcutaneous tumor models in nude mice. ResultsRECQL4 was upregulated in cervical cancer and correlated with prognosis, demonstrating a positive relationship with tumor mutational burden. Knockdown of RECQL4 inhibits cervical cancer cell proliferation, migration, and invasion, suppresses epithelial-mesenchymal transition status, induces cell cycle arrest, and promotes apoptosis. Mechanistically, RECQL4 mediated malignancy through the PI3K/AKT pathway and reduced nuclear β-catenin expression. In vivo studies further confirmed that RECQL4 knockout significantly inhibited tumor growth. ConclusionsOur findings provide novel insights into the mechanism behind RECQL4-mediated cervical cancer progression through the PI3K/AKT pathway. Furthermore, our study suggests potential therapeutic strategies for targeting RECQL4 in cervical cancer treatment.

APC mutations dysregulate alternative polyadenylation in cancer

BackgroundAlternative polyadenylation (APA) affects most human genes and is recurrently dysregulated in all studied cancers. However, the mechanistic origins of this dysregulation are incompletely understood.ResultsWe describe an unbiased analysis of molecular regulators of poly(A) site selection across The Cancer Genome Atlas and identify that colorectal adenocarcinoma is an outlier relative to all other cancer subtypes. This distinction arises from the frequent presence of loss-of-function APC mutations in colorectal adenocarcinoma, which are strongly associated with long 3′ UTR expression relative to tumors lacking APC mutations. APC knockout similarly dysregulates APA in human colon organoids. By mining previously published APC eCLIP data, we show that APC preferentially binds G- and C-rich motifs just upstream of proximal poly(A) sites. Lastly, we find that reduced APC expression is associated with APA dysregulation in tumor types lacking recurrent APC mutations.ConclusionsAs APC has been previously identified as an RNA-binding protein that preferentially binds 3′ UTRs during mouse neurogenesis, our results suggest that APC promotes proximal poly(A) site use and that APC loss and altered expression contribute to pervasive APA dysregulation in cancers.

Cancer genetic counseling via telegenetics and telephone: A qualitative study exploring the experience of patients and genetic counselors in an Australian cancer genetics context.

The demand for direct-to-patient (DTP) telegenetics (genetics services delivered via videoconferencing) in genetic counseling practice has rapidly increased, particularly since the COVID-19 pandemic. Recent telegenetics literature is mostly quantitative and not in the Australian context. A qualitative interview study was conducted to address this gap. This research investigated the experiences of patients and genetic counselors (GCs), enrolled in a randomized controlled trial, using telegenetics and telephone for cancer genetic counseling appointments. Twenty-eight semi-structured interviews with patients (n = 22) and GCs (n = 6) were conducted following patient randomization to either a telephone or telegenetics genetic counseling appointment. The interviews explored participant's experiences of telegenetics and compared DTP telegenetics with telephone and in-person delivery. Codebook thematic analysis was used to develop topic summaries from the data. Patient and GC participants noted positive experiences of telegenetics; with key benefits reported as reduced travel time, time and cost saving, ease, convenience, efficiency, and comfortability. Technical issues and privacy concerns were highlighted as potential disadvantages of telegenetics. All but one patient felt sufficiently emotionally supported while using telegenetics. Telegenetics has both benefits and limitations; however, generally, this cohort found telegenetics to be a suitable and acceptable mode of delivery for genetic counseling with many advantages over in-person or telephone appointments. Further studies should be conducted to provide evidence for the long-term implementation of telegenetics, regardless of any future COVID-19 pandemic lockdown restrictions.

Developing a prognostic model for hepatocellular carcinoma based on MED19 and clinical stage and determining MED19 as a therapeutic target

BackgroudMediator complex subunit 19 (MED19), a member of the mediator complex, has been demonstrated to involve in tumorigenesis of hepatocellular carcinoma (HCC). However, the regulation mechanisms of MED19, the immune landscape linking MED19 to HCC and its predictive value of immunotherapy treatment in HCC are so far unknown.MethodsHere, we analyzed data from The Cancer Genome Atlas and other databases to assess the expression of MED19 and its prognosis and therapeutical-targets impact in HCC.ResultsMED19 expression was upregulated in HCC tissues compared to non-tumorous liver tissues and that its upregulation was positively associated with advanced clinicopathology features. The multivariate analysis showed that MED19 was an independent predictor of outcome in HCC. In vitro experiments revealed that MED19 knockdown suppressed hepG2 cells proliferation, colony forming and invasion and induced apoptosis. Furthermore, MED19 inhibition resulted in G0/G1 phase arrest in hepG2 cells. We screened differentially expressed genes between low and high MED19 expression groups. Enrichment analyses showed that these genes were mainly linked to nuclear division and cell cycle. The pattern of tumor-infiltrating immune was demonstrated to be related with MED19 expression in HCC. TIDE analyses showed that patients in the low-expression group presented significantly better immunotherapy. Moreover, we developed a predicted model for HCC patient’s prognosis. Receiver operating characteristic analyses revealed that this model processed a favorable performance in predicting the prognosis of HCC patients. Finally, a nomogram was built for predicting survival probability of individual HCC patient.ConclusionThese findings suggest that MED19 as a novel biomarker that has significant association with immune landscape and immunotherapy response in HCC. The proposed prediction model composed of MED19 and pathological stage has a better role in determining prognosis and stratifying of HCC.

UBE2T is a diagnostic and prognostic biomarker for endometrial cancer.

Endometrial cancer (UCEC) is one of the most common malignant tumors in gynecology, and early diagnosis is crucial for its treatment. Currently, there is a lack of early screening tests specific to UCEC, and treatment advances are limited. It is crucial to identify more sensitive biomarkers for screening, diagnosis, and predicting UCEC. Previous studies have shown that UBE2T is involved in the development of various tumors such as breast cancer and liver cancer, but research on the role of UBE2T in UCEC is limited. Using data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and UALCAN databases, we analyzed the differential expression of UBE2T mRNA and protein in endometrial cancer (UCEC), along with its clinical relevance. A total of 113 clinical samples were collected, and immunohistochemistry and Western blot analysis were employed to validate bioinformatics analysis results. Volcano plots were generated using UBE2T and its differentially expressed genes, and a protein-protein interaction (PPI) network was constructed. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), and immune infiltration analysis were used to predict the functional role of UBE2T in UCEC progression. Correlation between UBE2T expression and patient survival was analyzed using TCGA data, and Kaplan-Meier survival curves were plotted. UBE2T is significantly overexpressed in UCEC and correlates with poor prognosis. Its overexpression is closely associated with mitosis, cell cycle regulation, and histological grade in UCEC patients. UBE2T is highly expressed in UCEC and suppresses anti-tumor immune responses in UCEC patients. It serves as a key participant in UCEC progression, associated with a range of adverse outcomes, and holds potential as a clinical diagnostic and prognostic biomarker.

6885 Glucose Utilization Differs Between RAS-like and BRAF-like Thyroid Cancer

Abstract Disclosure: S. Kumari: None. E. Chuki: None. J. Klubo-Gwiezdzinska: None. Background: RAS-like thyroid cancer (TC) tends to be more differentiated and less [1][8]Fluorodeoxyglucose Positron Emission Tomography-avid as compared with BRAF-like TC. Therefore, we hypothesized that glucose metabolism may differ between RAS-like and BRAF-like tumors and performed a study aimed at metabolomic profiling of TC. Methods: Based on Institutional Review Board approved protocol, we obtained fresh frozen human TC samples with corresponding normal tissue and performed targeted metabolomics including oxidative phosphorylation (OXPHOS), glycolysis and tricarboxylic acid (TCA) markers using mass spectrometry (MS). The Trusight 500 gene panel was used to determine molecular signature of tumors. Similarly, we performed targeted metabolomics of 4 BRAF-like and 2 RAS-like human TC cell lines. The data were analyzed using Ingenuity Pathway Analysis (Qiagen). We also analyzed mRNA expression of OXPHOS and glycolytic enzymes in 496 human TC tissue samples of The Cancer Genome Atlas (TCGA). The division into BRAF-like and RAS-like TC was based on well-established BRAF-RAS score (BRS) ranging from -1 to +1 for BRAF-like and RAS-like TC, respectively. Results: The study cohort consisted of 20 patients, 13 with BRAF-like and 7 with RAS-like tumors, aged 43±12 years old, 90% (18/20) females, with an average tumor size of 3±1.9 cm, multifocal growth in 55% (11/20) patients, central neck lymph node (LN) metastases in 55% (11/20), lateral neck LN metastases in 15% (3/20) patients and no distant metastases. The tumor size tended to be larger in RAS-like cohort (BRAF-like 2.27±1.28 vs RAS-like 4.34±2.52, p=0.08), and LN metastases more prevalent in BRAF-like cohort (BRAF-like 45% vs RAS-like 10%, p=0.08). Metabolomics data revealed that compared with normal thyroid, human TC tissue samples were characterized by an increased glucose metabolism (p&amp;lt;0.001), TCA (p&amp;lt;0.001) and gluconeogenesis (p&amp;lt;0.001). RAS-like tumors were characterized by a significantly higher TCA (p&amp;lt;0.001) and lower gluconeogenesis (p&amp;lt;0.001) as compared with BRAF-like tumors. Consistently, we found that TCA (p&amp;lt;0.001) and glucose metabolism (p&amp;lt;0.001) was higher in RAS-like vs BRAF-like cell lines. Transcriptomic profiling revealed that RAS-like TC was characterized by an increased expression of majority of tested OXPHOS enzymes compared to BRAF-like tumors, as evidenced by positive correlation with BRS, ranging from r = 0.28 to 0.54, p&amp;lt;0.001. Consistently, BRAF-like TC was associated with an upregulated mRNA expression of anaerobic glycolysis markers, with lactate dehydrogenase A, characterized by the highest negative correlation (r = -0.6, p&amp;lt;0.001) with BRS. Conclusion:RAS-like TC is more likely to utilize glucose through Krebs cycle, while BRAF-like tumors are more prone towards anaerobic glycolysis. Therapeutic strategies based on diverse metabolic profiles may provide a personalized approach to TC therapy. Presentation: 6/3/2024

8576 Genomic and Transcriptomic Characterization of Pediatric Thyroid Cancers

Abstract Disclosure: J.C. Ricarte-Filho: None. E.R. Reichenberger: None. K. Hinkle: None. A.R. Isaza: None. A.J. Bauer: None. A.T. Franco: None. Background: Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer in both pediatric and adult populations. Recent genomic profiling of papillary thyroid cancers, including that of the Cancer Genome Atlas, has uncovered the genetic alterations and molecular mechanisms driving thyroid cancer. However, these studies were primarily focused on adult patients. Despite their favorable prognosis, pediatric PTCs have higher rates of metastasis and recurrence than adult PTCs, but the molecular characterization of these tumors have been comparatively lacking. Methods: Here we explore the genomic and transcriptomic landscape of pediatric PTCs from 126 patients, including 107 primary tumors and 19 lymph node metastases (non-paired) using whole-exome sequencing and RNA sequencing. Thirteen primary tumors also had a paired lymph node metastasis analyzed. Results: We found driver alterations in 113 of 126 (90%) of the PTCs investigated, including the identification of a novel receptor tyrosine kinase (RTK) fusion not previously reported in thyroid cancer. Genetic drivers were predominantly kinase fusions (48%), most commonly fusions of RET (22%), NTRK3 (10%), ALK (5%) and NTRK1 (5%). The most common point mutations were BRAF p.V600E (21%), NRAS p.Q61R/K (9%) and hotspot mutations in DICER1 (4%). We found genetic alterations in 12 of the 13 paired lymph node metastasis. In all 12 cases the metastatic tissue harbored the same alterations found in the primary tumor. Eight out of 12 cases had fusions (3 RET, 3 NTRK3 and 2 NTRK1), and the additional 4 cases had point mutations (3 BRAFV600E and 1 TSHRM543T). Fourteen patients (11%) had widely invasive disease with lateral lymph node and distant metastases (N1bM1). Most of these N1bM1 tumors (13/14; 93%) were driven by RTK fusions (5 NTRK3, 3 RET, 3 NTRK1 and 2 ALK). The one case lacking a kinase fusion had a CHEK2 mutation. Conclusion: Our genomic and transcriptomic analysis allowed the detection of driver alterations in ∼90% of the cases, reducing the so-called “dark matter” in our cohort. Our data support that kinase fusions are associated with metastatic disease in pediatric PTC. Patients with RET/NTRK/ALK fusions have worse outcomes than those with BRAF p.V600E mutation and RAS-like alterations (NRAS, DICER1, non-V600 BRAF, PTEN). By using the transcriptional profiling generated in this study, we are currently investigating the molecular mechanisms underlying the metastatic behavior of pediatric PTCs harboring oncogenic fusions, including changes in MAPK transcriptional output, differentiation score and recruitment of signaling pathways potentially associated with the metastatic behavior of these tumors. Presentation: 6/3/2024

Predictive value of ZFHX4 mutation for the efficacy of immune checkpoint inhibitors in non-small cell lung cancer and melanoma.

Studies have shown that the Zinc finger homeobox 4 (ZFHX4) might be a factor in the prognosis of malignancies. However, little is known about the association between the ZFHX4 mutation and the effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and melanoma. Three public ICIs-treated NSCLC cohorts were divided into discovery cohort (n=75) and validation cohort (n=62), which were used to evaluate the relationship between ZFHX4 mutation and ICIs effectiveness in NSCLC. Seven ICIs-treated melanoma cohorts (n = 418) were used to analyze the relationship between ZFHX4 mutation and immunotherapy efficacy in melanoma. NSCLC and skin cutaneous melanoma (SKCM) cohorts from The Cancer Genome Atlas (TCGA) were used to investigate underlying mechanism. Patients with ZFHX4 mutant-type (ZFHX4-Mut) showed a superior objective response rate (ORR) (P < 0.01) and longer progression-free survival (PFS) (P < 0.05) than patients with ZFHX4 wild-type (ZFHX4-WT) in NSCLC cohorts. In the melanoma cohorts, patients carrying ZFHX4-Mut had a higher ORR (P = 0.042) and longer overall survival (OS) (P = 0.011). Besides, patients with NSCLC and melanoma harboring ZFHX4-Mut had a higher tumor mutation burden (TMB) (P<0.001) and tumor neoantigen burden (TNB) (P<0.001) than those harboring ZFHX4-WT. ZFHX4 mutation was associated with higher levels of plasma B cells, activated CD4+ memory T cells, and CD8+ T cells. Seven DNA damage repair pathways were significantly enriched in the ZFHX4-Mut group. ZFHX4 mutation could serve as a predicter for the efficacy of ICIs therapy in NSCLC and melanoma.

CHAC1 blockade suppresses progression of lung adenocarcinoma by interfering with glucose metabolism via hijacking PKM2 nuclear translocation.

Patients with lung adenocarcinoma (LUAD) generally have poor prognosis. Abnormal cellular energy metabolism is a hallmark of LUAD. Glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) is a member of the γ-glutamylcyclotransferase family and an unfolded protein response pathway regulatory gene. Its biological function and molecular regulatory mechanism, especially regarding energy metabolism underlying LUAD, remain unclear. By utilizing tissue microarray and data from The Cancer Genome Atlas and Gene Expression Omnibus, we found that CHAC1 expression was markedly higher in LUAD tissues than in non-tumor tissues, and was positively correlated with poor prognosis. Phenotypically, CHAC1 overexpression enhanced the proliferation, migration, invasion, tumor sphere formation, and glycolysis ability of LUAD cells, resulting in tumor growth both in vitro and in vivo. Mechanistically, through a shotgun mass spectrometry-based proteomic approach and high-throughput RNA sequencing, we found that CHAC1 acted as a bridge connecting UBA2 and PKM2, enhancing the SUMOylation of PKM2. The SUMOylated PKM2 then transferred from the cytoplasm to the nucleus, activating the expression of glycolysis-related genes and enhancing the Warburg effect. Lastly, E2F Transcription Factor 1 potently activated CHAC1 transcription by directly binding to the CHAC1 promoter in LUAD cells. The results of this study implied that CHAC1 regulates energy metabolism and promotes glycolysis in LUAD progression.

6897 The Role of Neutrophil Heterogeneity on T-cell Immunity in Advanced Thyroid Cancer Patients

Abstract Disclosure: Y. Kang: None. S. Lee: None. J. Yoon: None. D. Kang: None. J. Lee: None. Neutrophil heterogeneity is involved in autoimmune diseases, sepsis, and several cancers. However, the link between neutrophil heterogeneity and T-cell immunity in thyroid cancer is incompletely understood. We investigated the circulating neutrophil heterogeneity in 3 undifferentiated thyroid cancer (UTC), 14 differentiated thyroid cancer (DTC) (4 Stage IV, 10 Stage I-II), and healthy controls (n=10) by transcriptomic data and cytometry. Participants with UTC had a significantly higher proportion of immature high-density neutrophils (HDN) and lower proportion of mature HDN in peripheral blood compared to DTC. The proportion of circulating PD-L1+ immature neutrophils were significantly increased in advanced cancer patients. Unsupervised analysis of transcriptomics data from circulating HDN revealed downregulation of innate immune response and T cell receptor signaling pathway in cancer patients. Moreover, UTC patients revealed the upregulation of glycolytic process and glutamate receptor signaling pathway. Comparative analysis across tumor types and stages revealed the downregulation of various T cell related pathways, such as T cell receptor signaling pathway and T cell proliferation in advanced cancer patients. Moreover, the proportions of CD8+ and CD4+ T effector memory CD45RA+ (TEMRA) cells from peripheral blood were significantly decreased in UTC patients compared to DTC patients. Finally, we demonstrated that proportions of tumor infiltrated neutrophils were increased and related with poor prognosis in advanced thyroid cancer using data from our RNA-seq and TCGA (The Cancer Genome Atlas) data. In conclusion, observed prevalence of circulating immature high-density neutrophils and their immunosuppressive features in undifferentiated thyroid cancers underscore the importance of understanding neutrophil dynamics in the context of tumor progression in thyroid cancer. Presentation: 6/3/2024