The Cancer Genome Atlas Dataset Research Articles

Abstract PO2-08-05: ERBB2 mutated breast cancer detected by next generation sequencing: integrated analysis based on real-world data and The Cancer Genome Atlas

Abstract Background ERBB2 mutation has been recognized as an actionable target for pan-HER tyrosine kinase inhibitors in the era of precision medicine for solid tumors. In our real-world cohort utilizing next-generation sequencing (NGS), we successfully identified cases of ERBB2-mutated breast cancer. Furthermore, we investigated the clinical and pathological characteristics of these cases by integrating our data with The Cancer Genome Atlas (TCGA). Methods Our real-world cohort with NGS included 423 breast cancer patients treated at Gangnam Severance Hospital in Seoul, Republic of Korea, between April 2017 and January 2023. Among these patients, 13 were confirmed to have ERBB2 mutation through NGS analysis. We also incorporated data from TCGA database, which included 818 cases with ERBB2 sequencing. We compared the clinical characteristics (age, sex, stage, and ER, PR, and HER2 status) between the two groups. Furthermore, we examined the frequency of two of the most common mutations, PIK3CA and TP53, in both groups. Additionally, we investigated the distribution of PAM50 subtypes in the TCGA cohort. Results This study analyzed a total of 1,244 cases with NGS data. Among these cases, 31 (2.5%) exhibited ERBB2 mutation, with 13 patients identified in our dataset and 18 in the TCGA data. Among the 31 cases with ERBB2 mutation, 21 (67.7%) had HER2-negative disease. No significant differences were observed in other clinical characteristics based on ERBB2 status. Within the group of 31 ERBB2-mutated cases, TP53 mutations were found in 12 cases (38.7%), while PIK3CA mutations were found in 12 cases (38.7%). In the TCGA dataset, 4 cases (22.2%) with ERBB2 mutation were classified as HER2-E subtype, and the rate of HER2-E subtype was significantly higher in the ERBB2-mutated group compared to the ERBB2-wild group (22.2% vs. 7.6%, p=0.024). Conversely, 14 cases (77.8%) with ERBB2 mutation exhibited a non-HER2 enriched subtype. Conclusions Consistent with previous knowledge, ERBB2 mutations can be detected in HER2-negative breast cancer, despite their rarity. Furthermore, a considerable proportion of ERBB2-mutated breast cancer may depend on various oncogenic signaling pathways other than the HER2 pathway. Further studies are warranted to optimize therapeutic strategies for ERBB2-mutated breast cancer. Citation Format: Junghyun Kim, Yoonwon Kook, Seung Ho Baek, Min Ji Kim, Sohyun Moon, Seung Eun Lee, Jee Hung Kim, Soong June Bae, Joon Jeong, Sung Gwe Ahn. ERBB2 mutated breast cancer detected by next generation sequencing: integrated analysis based on real-world data and The Cancer Genome Atlas [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-08-05.

Abstract PO3-01-01: Dysregulation of Phenylalanine-tyrosine Metabolic Signaling Pathway and Neoadjuvant Response in HER2-positive Breast Cancer

Abstract Background: Although trastuzumab and tyrosine inhibitors combined with neoadjuvant chemotherapy could significantly improve patients' pathological complete response (pCR) rate, nearly half of the patients could not achieve complete remission. Our objective was to explore the relationship between metabolic signaling pathway changes and therapeutic efficacy in patients receiving neoadjuvant therapy for HER2-positive breast cancer. Methods: Core needle biopsy specimens from HER2-positive breast cancer patients who underwent neoadjuvant therapy and radical mastectomy at Fudan University Shanghai Cancer Center between January 2017 and December 2021 were collected for RNA sequencing. According to pathological evaluation, samples (n=133) were divided into pCR and non-pCR groups. Gene differences between the two groups were further evaluated for KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. The TCGA (The Cancer Genome Atlas, n=1091) and the HAN ethnic GEO datasets (GSE162228, GSE206, GSE48391, n=305) were used to analyze the metabolic differences between tumors and normal tissues with patients’ prognosis. Consensus clustering analysis was performed to divide patients for low and high phenylalanine-tyrosine metabolism dysregulation to analyze patients’ outcomes. The IC50 value of cell lines was tested using CCK-8 experiments. Western blot was performed to analyze the protein level changes in mTOR and glycolysis pathway. Results: We found that phenylalanine-tyrosine metabolism was significantly enriched in HER2-positive breast cancer patients. Consensus clustering analysis of TCGA and the HAN ethnic GEO datasets showed that patients with low phenylalanine-tyrosine catabolism had a significantly worse survival outcome than patients with high tyrosine metabolism (P= 0.017). In our cohort, phenylalanine-tyrosine pathway metabolic enzyme DDC was upregulated while MAOA was downregulated in non-pCR patients compared to pCR patients, suggesting the increased production of dopamine and reduced catabolism of dopamine (DA) in non-pCR tumors. In vitro experiments showed that dopamine and the knockdown of MAOA decreased cell sensitivity to pyrotinib. In addition, dopamine and clorgyline- an MAOA inhibitor, promoted the proliferation of HER2-positive cell lines under the treatment of pyrotinib. The GSEA analysis of our neoadjuvant cohort and TCGA datasets revealed that MAOA expression was associated with an inverse enrichment of the mTORC1 and glycolysis pathways. Western blot experiment results showed that dopamine or the knockdown of MAOA could activate the mTOR and glycolysis pathway Conclusions: Phenylalanine-tyrosine metabolism was significantly enriched in HER2-positive breast cancer patients. The phenylalanine-tyrosine signaling pathway may be dysregulated in HER2-positive breast cancer and patients with low phenylalanine-tyrosine catabolism have a worse prognosis. Low expression of MAOA promotes tumor resistance to HER2-targeted drugs and could serve as a therapeutic biomarker in breast cancer. Citation Format: Chih Wan Goh, Bingqiu Xiu, Jingyan Xue, Yayun Chi, Jiong Wu. Dysregulation of Phenylalanine-tyrosine Metabolic Signaling Pathway and Neoadjuvant Response in HER2-positive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-01-01.

Integrating trans-omics, cellular experiments and clinical validation to identify ILF2 as a diagnostic serum biomarker and therapeutic target in gastric cancer.

Gastric cancer (GC) lacks serum biomarkers with clinical diagnostic value. Multi-omics analysis is an important approach to discovering cancer biomarkers. This study aimed to identify and validate serum biomarkers for GC diagnosis by cross-analysis of proteomics and transcriptomics datasets. A cross-omics analysis was performed to identify overlapping differentially expressed genes (DEGs) between our previous aptamer-based GC serum proteomics dataset and the GC tissue RNA-Seq dataset in The Cancer Genome Atlas (TCGA) database, followed by lasso regression and random forest analysis to select key overlapping DEGs as candidate biomarkers for GC. The mRNA levels and diagnostic performance of these candidate biomarkers were analyzed in the original and independent GC datasets to select valuable candidate biomarkers. The valuable candidate biomarkers were subjected to bioinformatics analysis to select those closely associated with the biological behaviors of GC as potential biomarkers. The clinical diagnostic value of the potential biomarkers was validated using serum samples, and their expression levels and functions in GC cells were validated using in vitro cell experiments. Four candidate biomarkers (ILF2, PGM2L1, CHD7, and JCHAIN) were selected. Their mRNA levels differed significantly between tumor and normal tissues and showed different diagnostic performances for GC, with areas under the receiver operating characteristic curve (AUROCs) of 0.629-0.950 in the TCGA dataset and 0.736-0.840 in the Gene Expression Omnibus (GEO) dataset. In the bioinformatics analysis, only ILF2 (interleukin enhancer-binding factor 2) gene levels were associated with immune cell infiltration, some checkpoint gene expression, chemotherapy sensitivity, and immunotherapy response. Serum levels of ILF2 were higher in GC patients than in controls, with an AUROC of 0.944 for the diagnosis of GC, and it was also detected in the supernatants of GC cells. Knockdown of ILF2 by siRNA significantly reduced the proliferation and colony formation of GC cells. Overexpression of ILF2 significantly promotes the proliferation and colony formation of gastric cancer cells. Trans-omics analysis of proteomics and transcriptomics is an efficient approach for discovering serum biomarkers, and ILF2 is a potential diagnostic biomarker and therapeutic target of gastric cancer.

Boosting predictive models and augmenting patient data with relevant genomic and pathway information

The recurrence of low-stage lung cancer poses a challenge due to its unpredictable nature and diverse patient responses to treatments. Personalized care and patient outcomes heavily rely on early relapse identification, yet current predictive models, despite their potential, lack comprehensive genetic data. This inadequacy fuels our research focus—integrating specific genetic information, such as pathway scores, into clinical data. Our aim is to refine machine learning models for more precise relapse prediction in early-stage non-small cell lung cancer. To address the scarcity of genetic data, we employ imputation techniques, leveraging publicly available datasets such as The Cancer Genome Atlas (TCGA), integrating pathway scores into our patient cohort from the Cancer Long Survivor Artificial Intelligence Follow-up (CLARIFY) project. Through the integration of imputed pathway scores from the TCGA dataset with clinical data, our approach achieves notable strides in predicting relapse among a held-out test set of 200 patients. By training machine learning models on enriched knowledge graph data, inclusive of triples derived from pathway score imputation, we achieve a promising precision of 82% and specificity of 91%. These outcomes highlight the potential of our models as supplementary tools within tumour, node, and metastasis (TNM) classification systems, offering improved prognostic capabilities for lung cancer patients. In summary, our research underscores the significance of refining machine learning models for relapse prediction in early-stage non-small cell lung cancer. Our approach, centered on imputing pathway scores and integrating them with clinical data, not only enhances predictive performance but also demonstrates the promising role of machine learning in anticipating relapse and ultimately elevating patient outcomes.

Downregulation of NAT1 Expression is Associated with Poor Prognosis and Immune Infiltration in COAD.

An increasing corpus of evidence has identified the involvement of N-acetyltransferase 1 (NAT1), a member of the NAT family, in the progression of various cancers. However, the specific function of NAT1 in colon cancer (COAD) remains elusive. This study aims to decip her the role of NAT1 in COAD and its associated mechanisms. The Tumor Immunity Evaluation Resource (TIMER), The Cancer Genome Atlas (TCGA), and the Gene Expression Omnibus (GEO) databases were employed to assess the NAT1 expression level in COAD. The differential expression between COAD and normal colon tissue was further validated using quantitative real-time reverse-transcription PCR (RT-qPCR) and Western blot (WB) analyses. Additionally, survival analysis of NAT1 in COAD was carried out using the PrognoScan database and TCGA dataset. The functions of NAT1 were explored through gene set enrichment analysis (GSEA) and immuno-infiltration analysis. There was a significant reduction in NAT1 expression in COAD samples compared to normal tissue. Notably, low NAT1 expression in COAD correlated significantly with various clinical parameters such as tumor stage (T stage, N stage, M stage, pathologic stage), primary therapy outcome, carcinoembryonic antigen (CEA) level, and lymphatic invasion. The downregulation of NAT1 was also strongly linked with poor outcomes in overall survival (OS), progression-free interval (PFI), and disease-specific survival (DSS). Cox regression analysis highlighted NAT1 as an independent prognostic indicator for overall survival in COAD patients. GSEA results revealed NAT1's involvement in multiple pathways, including the neuroactive ligand-receptor interaction, olfactory transduction, olfactory signaling, extracellular matrix receptor interaction, calcium signaling, and focal adhesion pathways. Furthermore, NAT1 expression was found to significantly correlate with infiltration levels of various immune cells. The findings reveal NAT1's potential as a valuable prognostic biomarker for COAD. Moreover, its associated mechanisms offer insights that might pave the way for therapeutic interventions for COAD patients.

Exploring the role of interleukin 11 in cancer progression, patient survival, and therapeutic insights.

The Interleukin (IL)-11 gene, which is one of the members of the cytokine family, has an oncogenic role in some cancers. The main goal of this study is to analyze IL-11 expression level in 14 prevalent cancers and highlights its role in patients' survival, drug resistance, and sensitivities. Also, an association of this gene with metastasis and inflammation pathways has been investigated. Using the cancer genome atlas (TCGA) data, the level of IL-11 expression and its role in prognosis and survival rate were evaluated in 13 common cancers. Then, confirming the obtained in-silico outcomes, the relative expression level of this gene in colorectal cancer (CRC) samples and their adjusted tissues were assayed by the RT-qPCR method. Furthermore, to examine the association between IL-11 expression and drug resistance and sensitivity, PharmacoGX data was applied. The co-expression network was used to recognize the pathways in which IL-11 was involved. The results from the TCGA dataset indicated that the expression level of IL-11 increased significantly in 13 prevalence cancers compared to the control groups. Interestingly, this enhanced expression level is associated with a high rate of mortality in patients with bladder, stomach, colorectal, and endometrial cancers. Also, the co-expression network analysis showed a strong correlation between IL-11 and the genes of metastasis pathway and the genes related to the inflammation process. Finally, regarding drug sensitivity, IL-11 expression level can be introduced as a remarkable biomarker for cancer detection due to area under curve (AUC). Altered expression of the IL-11 gene is observed in 13 common cancers and is associated with prognosis and mortality rate in patients. Moreover, this gene can be considered a prognostic biomarker in different types of cancer, such as CRC.

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer. A linear regression model along with weighted gene co-expression network analysis (WGCNA) was applied on The Cancer Genome Atlas (TCGA) dataset to identify critical genes related to WGD. Further Cox regression models with random selection were used to optimize the most useful prognostic markers in the TCGA dataset. The clinical implication of the risk model was further assessed through prognostic impact evaluation, tumor stratification, functional analysis, genomic feature difference analysis, drug response analysis, and multiple independent datasets for validation. Our findings revealed a high aneuploidy burden, chromosomal instability (CIN), copy number variation (CNV), and mutation burden in breast tumors exhibiting WGD events. Moreover, 247 key genes associated with WGD were identified from the distinct genomic patterns in the TCGA dataset. A risk model consisting of 22 genes was optimized from the key genes. High-risk breast cancer patients were more prone to WGD and exhibited greater genomic diversity compared to low-risk patients. Some oncogenic signaling pathways were enriched in the high-risk group, while primary immune deficiency pathways were enriched in the low-risk group. We also identified a risk gene, ANLN (anillin), which displayed a strong positive correlation with two crucial WGD genes, KIF18A and CCNE2. Tumors with high expression of ANLN were more prone to WGD events and displayed worse clinical survival outcomes. Furthermore, the expression levels of these risk genes were significantly associated with the sensitivities of BRCA cell lines to multiple drugs, providing valuable insights for targeted therapies. These findings will be helpful for further improvement on clinical outcomes and contribution to drug development in breast cancer.

Abstract 3634: Copy number alterations in chromosome 19 genes associate with reduced immune infiltrate and adverse outcomes in lung cancer

Abstract Deleterious mutations in STK11/LKB1, KEAP1, and SMARCA4 have been shown to be associated with adverse response to immunotherapy in several lung cancer cohorts. However, the biological and clinical implications of deletions of these genes, which all reside on chromosome 19p (chr19p), has not been extensively described. We sought to first characterize the association between immune infiltration and these copy number changes in chr19p. To do this, we analyzed mutation, copy number, and gene expression data from non-small cell lung cancer cohorts in the Cancer Genome Atlas (TCGA). Chr19p is frequently deleted across cancers in the TCGA dataset, with higher rates in lung adenocarcinoma. In both lung adenocarcinoma and squamous cell carcinoma, nearly half of TCGA tumors have deletion of chr19p including STK11, KEAP1, and SMARCA4, and these tumors are enriched for STK11 mutation. Immune infiltrate (estimated by methylation patterns) was not significantly associated with STK11 mutation but was significantly reduced in tumors with chr19 deletion when controlling for tumor type and overall copy number load. In addition, low-level deletion of any of these genes correlated with decreased expression of immune signaling pathways. Based on these findings, we next wanted to characterize the association between chr19p copy number and immunotherapy response. We previously reported that low-level deletion of STK11 correlated with an immunosuppressive, treatment-refractory phenotype in samples collected from non-small cell lung cancer (NSCLC) patients with resectable disease in a phase II study of neoadjuvant atezolizumab + chemotherapy. To confirm these findings in a larger cohort, we examined the AACR GENIE NSCLC biopharma collective (BPC) dataset. A subset of this cohort included patients treated with immunotherapy (atezolizumab, nivolumab, and/or pembrolizumab) and with copy number data available or GISTIC analysis of individual genes (n = 204). Here, deletion of any of these three genes correlated with worse overall survival, and this was statistically significant for STK11 deletion. Overall, our data suggests that a broader set of patients, defined by copy number changes in these genes, may experience this adverse immunobiology. Further study to elucidate the mechanistic implications of this association is warranted. Citation Format: Brian S. Henick, Yohanna Georgis, Benjamin O. Herzberg, Carla P. Concepcion-Crisol, Alison M. Taylor. Copy number alterations in chromosome 19 genes associate with reduced immune infiltrate and adverse outcomes in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3634.

Abstract 3929: Comparative genomics of breast cancer in indigenous African and western populations first results from the E-Predict study

Abstract Breast cancer (BC) stands as the foremost female malignancy globally and is the most prevalent cancer in numerous developing countries, particularly in sub-Saharan Africa (SSA). Over the past decade, significant strides in comprehending the pathobiology of the disease and tumour dynamics have greatly enhanced treatment options, particularly in industrialized nations. Regrettably, SSA countries have witnessed only marginal, if any, improvements, with mortality rates surpassing incidence rates. Unfavourable outcome, early onset and high-grade tumours are predominant in SSA. Despite these challenging clinical phenotypes, there is currently a limited understanding of the primary molecular drivers, primarily due to a dearth of reliable data. Furthermore, there is a paucity of research conducted in, and pertinent to, the challenges of the disease in low-income countries (LICs), despite a rising incidence and higher mortality-to-incidence ratios. We thus established an international translational cancer research consortium in five distinct African countries. This initiative has contributed to the creation of a high-quality repository of biomaterials. Additionally, we have conducted whole exome sequencing on the initial 100 cases of breast cancer, comparing the molecular architecture of these tumors with data from The Cancer Genome Atlas (TCGA). We examining and compared the clinical disease phenotypes between indigenous African women and Western patients. A higher proportion of grade III tumors was observed in African patients aged between 30 to 59 years as compared to other patients within the same age group. In comparative molecular analyses, we found a significantly elevated tumor mutational burden in African patients (median of >15/MB) in contrast to other populations within the TCGA (median ~ 0.7/MB). Gene sets featuring co-occurring mutations, predicted to be associated with survival using the TCGA dataset, showed high mutation rates in the African cohort. Notably, co-occurring mutations between PIK3CA and genes linked to genomic instability, such as BIRC6 (HR: 11.7, p = 2.7e-05), KMT2C (HR: 4.7, p = 4.01e-04), NEB (HR: 3.84, p = 0.48), and PCLO (HR: 4.9, p = 0.016), among others, strongly correlated with poor overall survival and were highly mutated within the African cohort. Interestingly, within the TCGA, patients with early breast cancer onset exhibit twice as many mutations in KMT2C, a gene known for its association with DNA damage repair, genomic instability, and showed an improved response to immune checkpoint inhibition. These initial findings suggest that breast cancer genomics in indigenous African populations may exhibit substantial differences, potentially warranting consideration for distinct therapeutic modalities for these patients. Citation Format: Smiths Sengkwawoh Lueong, Pamela Derliche Tonouo Derliche Tonouo, Arnol Auvaker Tiofack, Rovaldo Nguims Kenfack, Jules Roger Kuiate, Esther Dina Mbassi, Sidonie Noa Ananga, Etienne Okobalemba Atenguena, Gustave Simo, Abdel Jelil Njouendou, Walters Ndaka, Zacharie Sando, Emmanuella Mayemi, Rachel Tayou, Gilles Gael Aghoagni, Anne Sango, Benjamin Pokam, Augustin Tozoula Bambara, Jens T. Siveke. Comparative genomics of breast cancer in indigenous African and western populations first results from the E-Predict study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3929.

ENO1 contributes to the gemcitabine resistance of pancreatic cancer through the YAP1 signaling pathway.

Pancreatic cancer (PC), a leading cause of cancer-related deaths, has a 5-year survival rate of approximately 10%. α-Enolase (ENO1) is a junction channel protein involved in tumor cell apoptosis and chemoresistance. However, the role of ENO1 in PC remains unclear. The expression and prognosis of ENO1 levels were determined in PC using public databases based on The Cancer Genome Atlas (TCGA) data sets. Cell viability, half maximal inhibitory concentration (IC50), autophagy, apoptosis, and autophagy markers were examined using cell counting kit-8 (CCK-8), transmission electron microscope, flow cytometry assays, and immunoblot, respectively. Using the Gene Expression Omnibus (GEO) and TCGA data sets, we found that ENO1 was significantly enriched in PC tumor tissues, and high expression levels of ENO1 were associated with an unfavorable prognosis. Whereas ENO1 silencing suppressed proliferation, autophagy, and induced cell apoptosis in PC cells, and inhibited tumor growth in vivo. Mechanistically, knockdown of ENO1 enhanced cellular cytotoxicity of gemcitabine (GEM), as well as reducing the expression of yes-associated protein 1 (YAP1), a major downstream effector of the Hippo pathway in vitro. YAP1 promoted autophagy and protected PC cells from GEM-induced apoptotic cell death. Furthermore, YAP1 overexpression attenuated the inhibition effects of ENO1 silencing. Our results suggest that ENO1 overexpression promotes cell growth and tumor progression by increasing the expression of YAP1 in PC. Further studies are required to understand the detailed mechanisms between ENO1 and YAP1 in PC.

Abstract 5872: CDK1-SOX9 axis contributes to chemotherapy resistance in gastric cancer

Abstract Gastric carcinoma (GC) is the third most prevalent cause of cancer-related mortality worldwide, presenting a formidable challenge with the rise of resistance to chemotherapeutic agents, leading to treatment failures. Cyclin-dependent kinase 1 (CDK1) has garnered attention due to its substantial overexpression in various tumors, including GC, and its association with poor overall survival and relapse-free survival. This study aimed to understand the molecular and functional mechanisms underlying the CDK1-SOX9 axis in GC chemotherapy resistance. Through a comprehensive analysis of data from The Cancer Genome Atlas (TCGA) and our own integrated gene expression study, we found a positive correlation between CDK1 and SOX9 in both human and mouse GC tissues (p<0.001). Additionally, conserved alterations in miRNAs have been identified in the context of gastric carcinogenesis, evident in our local cohort and the TCGA dataset. Our in-depth investigation of premiR-145 has shed light on the existence of several CpG nucleotides. Notably, treatment with a DNMT inhibitor (5-Aza) has triggered the upregulation of miR-145 expression. Furthermore, the ectopic expression of CDK1 has been associated with increased DNMT1 phosphorylation and enhanced enzymatic activity. Conversely, silencing CDK1 reversed this effect, and the inhibition of DNMT1 reduced SOX9 protein expression. Using cisplatin-resistant cell lines revealed a significant increase in CDK1 and SOX9 expression where silencing CDK1 and SOX9 sensitized these cells to chemotherapy. This study provides valuable insights into the intricate mechanisms governing the CDK1-SOX9 axis in GC chemotherapy resistance, providing potential avenues for therapeutic interventions in this challenging malignancy. Citation Format: Marwah M. Al-Mathkour, Shoumin Zhu, Melanie Genoula, Wael El-Rifai. CDK1-SOX9 axis contributes to chemotherapy resistance in gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5872.

Abstract 3040: Tumor-specific super-enhancer drives overexpression of EVI1 in ovarian cancer

Abstract Epithelial ovarian cancer (OC) is typically diagnosed at a late stage and, despite treatment with cytoreductive surgery and chemotherapy, 70-80% of patients relapse and eventually die due to the disease. Major challenges to improve patient outcomes are to overcome therapy resistance and to individually tailor therapy. Uncovering the molecular drivers of OC, especially in the most common subgroup high-grade serous (HGS), will help develop novel therapeutic strategies to meet these challenges. Using the Cancer Genome Atlas (TCGA) data, we observed that a locus in 3q26.2, near the EVI1 oncogene, was the most significantly amplified region in HGS OC, occurring in more than 80% of those tumors. We validated these findings in an OC dataset from the Hartwig Medical Foundation and in OC cell lines from the DepMap database. Furthermore, HGS OC had the highest mean copy number of the 3q26.2 locus co-occurring with high mean EVI1 expression among all tumor entities in the pan-cancer TCGA dataset. These EVI1 expression levels are significantly higher than in normal fallopian tube, from which HGS OC most likely arises. EVI1 overexpression promotes leukemogenesis in 3q26-rearranged acute myeloid leukemia (AML), as a result of chromosomal translocations that enable hijacking of hyperactive enhancers. Here, we hypothesize that EVI1 also plays a crucial role in OC development, but that its aberrant expression in this disease is driven by the amplification of yet undiscovered regulatory elements near EVI1. We showed that EVI1-positive OC cell lines, of which the majority are HGS, are EVI1-dependent and harbor a ~200 kb amplified region near EVI1. This region interacts with the EVI1 promoter (4C-Seq), is characterized by open chromatin (ATAC-Seq), and shows high levels of H3K27 acetylation (H3K27ac ChIP-Seq), suggesting the presence of an active enhancer. Furthermore, based upon H3K27ac signal, we identified within this region a super-enhancer of approximately 65 kb. In OC cell lines without detectable EVI1 levels or cell lines from other cancer subtypes, such as breast and colon cancer, this location had no active enhancer and did not loop to the EVI1 promoter. Altogether, these data point to the generation of a hyperactive super-enhancer driving EVI1 overexpression in OC. These findings emphasize the importance of epigenetic control in the regulation of EVI1 expression, as previously shown in 3q26-rearranged AML. Since OC tumor cell lines are strongly dependent on EVI1, interference with this super-enhancer, leading to loss of EVI1 expression, could be exploited to inhibit tumor growth. For this purpose, we generated GFP-tagged EVI1 cell line models (e.g. SKOV3), which will be used to discover small molecules to target the activity of this super-enhancer. In conclusion, we discovered a new mechanism of enhancer-mediated overexpression of the EVI1 oncogene as a molecular driver in ovarian cancer, with possible implications for therapy. Citation Format: Leonie Smeenk, Sabrina Kruse, Roger Mulet-Lazaro, Ingrid Boere, John Martens, Stefan Gröschel, Claudia Scholl, Stefan Fröhling, Ruud Delwel. Tumor-specific super-enhancer drives overexpression of EVI1 in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3040.

Abstract 2266: Detection of androgen receptor splice variants from clinical sequencing

Abstract Background: Androgen receptor splice variant-7 (AR-v7) has been widely studied as a biomarker of resistance to AR-targeted therapy in castration-resistant prostate cancer (CRPC). Various methods have been used to detect AR-v7 in CRPC specimens, including next generation sequencing (NGS) technology. However, NGS technologies applied in clinical sequencing have focused on using blood or fresh-frozen CRPC tissue specimens. There is not yet an AR-v7 detection system tailored to formalin-fixed paraffin-embedded (FFPE) tissue specimens commonly used for clinical sequencing in hospitals. Methods: In this respect, we propose a novel approach to identify AR-v7 in targeted RNA sequencing (RNA-seq) data derived from FFPE specimens. This approach can identify, in addition to AR-v7, all constitutively active AR splice variants (AR-Vs) that are co-expressed with AR-v7. In short, our two-step approach first gathers soft-clipped or divided reads that are adjacent to the splicing sites of AR-Vs and then yields the number of splitting reads that support the existence of AR-Vs. Next, the algorithm selects the paired-end reads whose one side and the other side are mapped to the preceding and following exons, respectively. The final number of spanning reads are calculated following to the removal of low-quality reads. Results: We validated the proposed approach using two large-scale, independent RNA-seq datasets of prostate cancer (PC) samples: 111 samples from Seoul National University Hospital (SNUH) and 558 samples from The Cancer Genome Atlas (TCGA) dataset. The majority of both datasets were localized PC tumors, especially in the SNUH dataset, where localized PC accounted for 91% of the total. Overall, our approach successfully identified samples with putative AR-Vs, including AR-v7, AR-v3, and AR-v9. Statistical analyses of 111 SNUH PC patients suggested potential detection threshold in clinical sequencing settings (at least 200 split reads). In the SNUH dataset, the AR-v7 positive group, which included 5 patients (5%) with values above the threshold, shared the following characteristics: higher AR-v7/full length AR expression levels, AR amplification and co-expression with AR-v3/AR-v9. AR-v7 positivity was experimentally validated by Sanger sequencing. The similar pattern was also found in the analysis of TCGA dataset. Conclusions: These results demonstrate that the detection system can successfully identify AR-v7 positivity not only for metastatic PC but also for patients with localized PC through clinical sequencing. We expect that the further in-depth analyses including larger samples and clinical outcomes can discover clinical applicability of AR-v7. Citation Format: Suhyun Hwangbo, Sungyoung Lee, Sheehyun Kim, Hongseok Yun. Detection of androgen receptor splice variants from clinical sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2266.

Abstract 7020: Prognostic implications of microRNA 181a 2 3p expression in association with tumor budding in patients with stage III lung squamous cell carcinoma

Abstract Introduction: Tumor budding (Bd) has been known as an independent prognostic factor in various malignancies. MicroRNA (miRNA) are known to play an important role in regulating Bd. However, understanding the relationship between Bd and miRNA in Lung Squamous cell carcinoma (LUSC) remains limited. Methods: 115 LUSC patients who underwent curative resection were included in the discovery cohort. Bd was verified through immunohistochemical (IHC) stain. Bd was classified according to a three tier system: Bd1 with 0-4 buds, Bd2 with 5-9 buds, and Bd3 with 10 or more buds. MiRNA expression profiles were analyzed through RNA sequencing. Differences in survival outcomes for miRNA, as identified in the discovery cohort, were confirmed using LUSC data of The Cancer Genome Atlas (TCGA) as a validation cohort. Results: The relationship between Bd2 and the prolongation of recurrence-free survival (RFS) was statistically significant (p=0.0113), whereas Bd1 was correlated with Overall Survival (OS) (p=0.0468). Multivariate analysis indicated that both a high T stage (HR: 5.211, 95% CI: 1.168-23.250, p = 0.031; and HR: 5.107, 95% CI: 1.447-18.030, p < 0.011) and Bd3 (HR: 3.683, 95% CI: 1.370-9.900, p = 0.010; and HR: 1.600, 95% CI: 0.800-3.201, p = 0.018) are independently significant poor prognostic factors for both RFS and OS. MiRNA-181a-2-3p was identified through Differentially Expressed miRNA (DER) analysis. A higher expression of miRNA-181a-2-3p in stage III LUSC of the TCGA dataset was associated with OS (p=0.0463). Conclusions: Our study demonstrates that the miRNA 181a 2 3p expression is associated with improved OS. This association may be attributed to its inhibitory effect on Bd in advanced stages of LUSC. Citation Format: Eunhyo Lee, Seoree Kim, Jeana Kim, Minho Lee, Yoonho Ko, Sang Hoon Chun. Prognostic implications of microRNA 181a 2 3p expression in association with tumor budding in patients with stage III lung squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7020.

Abstract 4958: Optimizing transcriptome-based synthetic lethality predictions to improve precision oncology in breast cancer: BC-SELECT

Abstract Introduction: Precision oncology currently focuses on targeting specific mutations in cancer driver genes as predictors of treatment response. Clinical application of tumor transcriptomics is similarly limited to using specific RNA-based fusions for using therapy. SELECT (Lee et al, Cell 2021) is a computational tool that characterizes synthetic-lethal and/or synthetic-rescue genetic interactions of potential drug targets by using expression data, then uses these interactions to predict drug response in cancer patients. SELECT was initially developed using pan-cancer data from The Cancer Genome Atlas (TCGA), with limited evaluation on agents in breast cancer. We therefore sought to optimize SELECT for patients with breast cancer in an adaptation named BC-SELECT. Methods: The standard SELECT comprises two steps: (1) Using an in-vitro screen, a patient tumor data screen, and a phylogenetic screen to build a library of clinically relevant candidate synthetic-lethal/synthetic-rescue gene partners; and (2) Generating scores based on gene partners’ expression levels in a given sample. Scores are then used to predict the likelihood of response to a given therapy. For BC-SELECT, we modified this framework as follows: We incorporated the METABRIC dataset, comprising 1,989 samples and used only the breast cancer-specific TCGA dataset (1,075 samples) (which outperformed training on pan-cancer TCGA). To enhance the survival screening process, we include up to 5 clinical covariates for each training dataset, and prioritized gene pairs based on survival. Furthermore, we introduced new scoring controls to confirm prediction accuracy. All parameters have been standardized to optimize performance. Results: BC-SELECT predicted treatment response in our initial cohort of breast cancer trials with immunotherapy or targeted therapy and expression data, where the same treatment/treatment target was present in more than one trial. BC-SELECT prediction was more accurate for immunotherapy and PARP inhibitors compared to trastuzumab. The AUC ranges for immunotherapy are between 0.67 and 0.83. For PARP inhibitors, the AUC ranges from 0.5 to 0.78, and for trastuzumab, it falls between 0.5 and 0.75. Discussion: BC-SELECT advances transcriptome-based synthetic lethality prediction for translational use in patients with breast cancer. This tool demonstrates analytic and clinical validity to begin to improve therapy stratification and prioritization in patients. Citation Format: Yewon Kim, Matthew Nagy, Rebecca Pollard, Nishanth Ulhas Nair, Lipika Ray, Eytan Ruppin, Padma Sheila Rajagopal. Optimizing transcriptome-based synthetic lethality predictions to improve precision oncology in breast cancer: BC-SELECT [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4958.

Validation of CDC45 as a novel biomarker for diagnosis and prognosis of gastric cancer.

Cell division cycle protein 45 (CDC45) has been demonstrated to play vital roles in the progression of various malignancies. However, the clinical significance of CDC45 in gastric cancer (GC) remains unreported. In this study, we employed the TCGA database and the TCGA & GTEx dataset to compare the mRNA expression levels of CDC45 between gastric cancer tissues and adjacent or normal tissues (p < 0.05 was considered statistically significant), which was further validated in multiple datasets including GSE13911, GSE29272, GSE118916, GSE66229, as well as RT-qPCR. Furthermore, we harnessed the Human Protein Atlas (HPA) to evaluate the protein expression of CDC45, which was subsequently verified through immunohistochemistry (IHC). To ascertain the diagnostic utility of CDC45, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were calculated in TCGA database, and further validated it in TCGA & GTEx and GSE66229 datasets. The Kaplan-Meier method was used to reveal the prognostic importance of CDC45 in The Cancer Genome Atlas (TCGA) database and authenticated through the GSE66229, GSE84433, and GSE84437 datasets. Through cBioPortal, we identified co-expressed genes of CDC45, and pursued enrichment analysis. Additionally, we availed gene set enrichment analysis (GSEA) to annotate the biological functions of CDC45. Differential expression analysis revealed that CDC45 was significantly upregulated at both the mRNA and protein levels in GC (all p < 0.05). Remarkably, CDC45 emerged as a promising prognostic indicator and a novel diagnostic biomarker for GC. In a comprehensive the drug susceptibility analysis, we found that patients with high expression of CDC45 had high sensitivity to various chemotherapeutic agents, among which 5-fluorouracil, docetaxel, cisplatin, and elesclomol were most evident. Furthermore, our findings suggested a plausible association between CDC45 and immune cell infiltration. Enrichment analysis revealed that CDC45 and its associated genes may play crucial roles in muscle biofunction, whereas GSEA demonstrated significant enrichment of gene sets pertaining to G protein-coupled receptor ligand binding and G alpha (i) signaling events. Our study elucidates that upregulation of CDC45 is intricately associated with immune cell infiltration and holds promising potential as a favorable prognostic marker and a novel diagnostic biomarker for GC.

Cuproptosis-related gene-located DNA methylation in lower-grade glioma: Prognosis and tumor microenvironment.

Cuproptosis a novel copper-dependent cell death modality, plays a crucial part in the oncogenesis, progression and prognosis of tumors. However, the relationships among DNA-methylation located in cuproptosis-related genes (CRGs), overall survival (OS) and the tumor microenvironment remain undefined. In this study, we systematically assessed the prognostic value of CRG-located DNA-methylation for lower-grade glioma (LGG). Clinical and molecular data were sourced from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We employed Cox hazard regression to examine the associations between CRG-located DNA-methylation and OS, leading to the development of a prognostic signature. Kaplan-Meier survival and time-dependent receiver operating characteristic (ROC) analyses were utilized to gauge the accuracy of the signature. Gene Set Enrichment Analysis (GSEA) was applied to uncover potential biological functions of differentially expressed genes between high- and low-risk groups. A three CRG-located DNA-methylation prognostic signature was established based on TCGA database and validated in GEO dataset. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves in the TCGA dataset were 0.884, 0.888, and 0.859 while those in the GEO dataset were 0.943, 0.761 and 0.725, respectively. Cox-regression-analyses revealed the risk signature as an independent risk factor for LGG patients. Immunogenomic profiling suggested that the signature was associated with immune infiltration level and immune checkpoints. Functional enrichment analysis indicated differential enrichment in cell differentiation in the hindbrain, ECM receptor interactions, glycolysis and reactive oxygen species pathway across different groups. We developed and verified a novel CRG-located DNA-methylation signature to predict the prognosis in LGG patients. Our findings emphasize the potential clinical implications of CRG-located DNA-methylation indicating that it may serve as a promising therapeutic target for LGG patients.

A novel PD-1/PD-L1 pathway-related seven-gene signature for the development and validation of the prognosis prediction model for breast cancer.

Breast cancer (BC/BRCA) is the most common carcinoma in women. The average 5-year survival rate of BC patients with stage IV disease is 26%. A considerable proportion of patients still do not receive effective therapy. It is an unmet need to identify novel biomarkers for BC patients. Herein, we evaluated whether the programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) status is associated with the clinical outcomes of BC, based on data from The Cancer Genome Atlas (TCGA). Clinical and transcriptome data of BC patients were obtained from TCGA dataset, and prognostic genes in BC patients were identified, as well as the PD-1/PD-L1 pathway mainly associating with the BC patients. Following the execution of the consensus clustering algorithm, BC patients were segregated into two clusters, and subsequent investigation of the potential mechanisms between them was carried out. A comparison of ferroptosis and N6-methyladenosine (m6A) was conducted between the two groups with the greatest difference in prognosis. Based on least absolute shrinkage and selection operator (LASSO) analysis, a signature associated with the PD-1/PD-L1 pathway was developed, and the prognosis outcome and the predictive accuracy of the signature model were further assessed. Prognostic genes in BC patients were studied using TCGA data and it was found that the PD-1/PD-L1 pathway was most associated with the BC patients. Then, a low-risk (C1) group and a high-risk (C2) group of BC patients were constructed based on a PD-1/PD-L1 pathway-related signature. The functional analyses suggested that the underlying mechanisms between these groups were mainly associated with immune-related pathways. We found that ferroptosis and m6A were significantly different between the two groups. A PD-1/PD-L1 pathway-related gene signature was further developed to predict survival of BC patients, including 7 genes [mitogen-activated protein kinase kinase 6 (MAP2K6), NF-kappa-B inhibitor alpha (NFKBIA), NFKB Inhibitor Epsilon (NFKBIE), Interferon gamma (IFNG), Toll/interleukin-1 receptor domain-containing adapter protein (TIRAP), IkappaB kinase (CHUK), and Casein kinase 2 alpha 3 gene (CSNK2A3)]. The receiver operating characteristic (ROC) curves were analyzed to further assess the prognostic values of these 7 genes. The 1-, 3-, and 5-year values of the areas under the curve (AUCs) for overall survival were 0.651, 0.658, and 0.653 in this seven gene signature model, respectively. PD-1/PD-L1 pathway-related subtypes of BC were identified, which were closely associated with the immune microenvironment, the ferroptosis status, and m6A in BC patients. The gene signature involved in the PD-1/PD-L1 pathway might help to make a distinction and predict prognosis in BC patients.

Comprehensive analyses of m1A regulator-mediated modification patterns determining prognosis in lower-grade glioma (running title: m1A in LGG)

N1-methyladenosine (m1A) modification is a crucial post-transcriptional regulatory mechanism of messenger RNA (mRNA) in living organisms. Few studies have focused on analysis of m1A regulators in lower-grade gliomas (LGG). We employed the Nonnegative Matrix Factorization (NMF) technique on The Cancer Genome Atlas (TCGA) dataset to categorize LGG patients into 2 groups. These groups exhibited substantial disparities in terms of both overall survival (OS) and levels of infiltrating immune cells. We collected the significantly differentially expressed immune-related genes between the 2 clusters, and performed LASSO regression analysis to obtain m1AScores, and established an m1A-related immune-related gene signature (m1A-RIGS). Next, we categorized all patients with LGG into high- and low-risk subgroups, predictive significance of m1AScore was confirmed by conducting univariate/multivariate Cox regression analyses. Additionally, we confirmed variations in immune-related cells and ssGSEA and among the high-/low-risk subcategories in the TCGA dataset. Finally, our study characterized the effects of MSR1 and BIRC5 on LGG cells utilizing Edu assay and flow cytometry to explore the effects of modulation of these genes on glioma. The results of this study suggested that m1A-RIGS may be an excellent prognostic indicator for patients with LGG, and could also promote development of novel immune-based treatment strategies for LGG. Additionally, BIRC5 and MSR1 may be potential therapeutic targets for LGG.

Ferroptosis-Related Genes Are Associated with Radioresistance and Immune Suppression in Head and Neck Cancer.

Background: Ferroptosis is associated with tumor development; however, its contribution to radioresistant head and neck cancer (HNC) remains unclear. In this study, we used bioinformatics analysis and in vitro testing to explore ferroptosis-related genes associated with HNCs radiosensitivity. Materials and Methods: GSE9714, GSE90761, and The Cancer Genome Atlas (TCGA) datasets were searched to identify ferroptosis-related differentially expressed genes between radioresistant and radiosensitive HNCs or radiation-treated and nonradiation-treated HNCs. A protein-protein interaction analysis on identified hub genes was then performed. Receiver operating characteristic curves and Kaplan-Meier survival analysis were used to assess the diagnostic and prognostic potential of the hub genes. Cell counting kit-8, transwell assay, and flow cytometry were applied to examine the role of hub gene collagen type IV, alpha1 chain (COL4A1) on the proliferation, migration, invasion, and apoptosis of TU686 cells. Results: Hub genes MMP10, MMP1, COL4A1, IFI27, and INHBA showed diagnostic potential for HNC and were negatively correlated with overall survival and disease-free survival in the TCGA dataset. Also, IL-1B, IFI27, INHBA, and COL4A1 mRNA levels were significantly increased in TCGA patients with advanced clinical stages or receiving radiotherapy, whereas COL4A1, MMP10, and INHBA expressions were negatively correlated with immune infiltration. Furthermore, the knockdown of COL4A1 inhibited cell proliferation, migration, and invasion while promoting apoptosis in TU686 cells. Conclusion: Ferroptosis-related hub genes, such as COL4A1, are potential diagnostic and prognostic indicators as well as therapeutic targets for HNC.