Pan Cancer Research Articles

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes.

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored. We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity. We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers. Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Molecular pathogenesis of microsatellite instability-high early-stage colorectal adenocarcinoma in India.

The prevalence of microsatellite instability (MSI) subtype among all colon cancers in India is about 30 %, approximately two times more than that of western population suggesting different molecular pathogeneses. A NanoString analysis-based Pan cancer differential expression (DE) profile was determined in a primary cohort of early-stage CRC (tumor=10, normal=7), and correlated against MSI status. Using RT-PCR, tumor-specific DE genes were validated in another cohort of MSI-high CRC (n=15). Among the most differentially expressed genes, AXIN2, ETV4, and RNF43 were tumor cell-specific signals, while a set of genes including COL11A1, COMP, INHBA, SPP1, MMP3, TLR2, and others were immune cell-specific signals, that had a differential expression between MSI and MSS groups. When overlapped with The Cancer Genome Atlas (TCGA) studies using the Tumor immune estimation resource tool (TIMER), and protein-protein interaction analysis by STRING.db, these genes were segregated to representative tumor cells and immune cells. On validation, the tumor-specific gene signals were inversely associated with TLR4 expression. The differential expression distribution of AXIN2, ETV4, and RNF43 among tumor and immune cells, suggests more than one pathological subset in the MSI-H subgroup of early-stage CRC in the Indian population.

Pan Cancer Analysis Indicates TREM2 as a Target for Cancer Treatment

Pan Cancer Analysis Indicates TREM2 as a Target for Cancer Treatment

Identification of Cuproptosis-related Gene Lipoyltransferase 1 as a Promising Biomarker in Oral Squamous Cell Carcinoma.

To find efficient cuproptosis-related biomarkers to explore the oncogenesis and progression of oral squamous cell carcinoma (OSCC). All the original data were downloaded from the Cancer Genome Atlas (TCGA) database. Univariate Cox analysis and Kaplan-Meier survival analysis were used to identify the gene related to survival. Tumor Immune Estimation Resource 2.0 (TIMER 2.0) was used to reveal the different expression of cuproptosis-related gene lipoyltransferase 1 (LIPT1) in various kinds of tumours. LIPT1, as a cuproptosis-related gene, was found to be differentially expressed in the OSCC group and the control group. It was also found to be related to the prognosis of OSCC. Pan cancer analysis showed LIPT1 was also involved in various kinds of tumours. All the results demonstrate that the cuproptosis-related gene LIPT1 is highly involved in the oncogenesis and progression of OSCC. These findings give new insight for further research into the cuproptosis-related biomarkers in OSCC.

High TLX1 Expression Correlates with Poor Prognosis and Immune Infiltrates in Patients with Lung Adenocarcinoma.

To develop optimal personalized therapy for lung adenocarcinoma (LUAD), potential biomarkers associated with the prognosis are urgently needed. It is unclear what role T Cell Leukemia Homeobox 1 (TLX1) plays in LUAD. In this study, TLX1's relationship with LUAD was investigated using TCGA database analysis, bioinformatics analysis, and experimental validation. We examined the expression of TLX1 in pan cancer and LUAD, the relationship between TLX1 expression and clinical features, immune infiltration, its diagnostic and prognostic value, as well as TLX1 related pathways. The analysis included various statistical methods, including the Kaplan-Meier method, Cox regression analysis, GSEA, and immune infiltration analysis. TLX1 expression in LUAD cell lines was validated using qRT-PCR. In LUAD patients, high expression of TLX1 was associated with T stage (P<0.001). High TLX1 expression was associated with worse overall survival (OS) (HR: 1.57; 95% CI: 1.18-2.1; P=0.002). And TLX1 HR: 1.619; 95% CI: 1.012-2.590; P=0.044) was independently correlated with OS in LUAD patients. TLX1 expression was associated with the pathways, including Rho GTPase effectors, DNA repair, TCF dependent signaling in response to WNT, signaling by Nuclear Receptors, signaling by Notch, chromatin-modifying enzymes, ESR-mediated signaling, cellular senescence, and transcriptional regulation by Runx1. TLX1 expression was correlated with aDC, Tcm, and TReg cells. The expression of TLX1 was significantly increased in LUAD cells compared to BEAS-2B cells. An association between high TLX1 expression and poor survival and immune infiltration was found in LUAD patients. There may be a potential role for TLX1 in diagnosis, prognosis, and immunotherapy for LUAD.

Co-occurrence of germline pathogenic variants in a Brazilian cohort of patients with breast cancer.

e22532 Background: The estimated prevalence of germline pathogenic variants (PV) or likely pathogenic variants (LPV) in high and moderate penetrance genes is around 7-10% among women with breast cancer (BC). The emergence of next-generation sequencing (NGS) technology allowed multi-gene panel testing (MGPT) analysis at a lower cost. However, the detection of incidental findings with unknown significance (VUS) and challenges with variant interpretation increase substantially with MGPT. The effect of co-existing PV/LPV in two or more genes is still understudied. Here, we present the prevalence of concurrent germline LPV/PV in a cohort of Brazilian women with BC who underwent a MGPT in a single reference laboratory. Methods: Retrospective observational study using a laboratory cohort (Oncoclínicas Precision Medicine). This study includes women with BC who performed a germline MGPT (able to call SNVs, indels and CNVs) from 2019 to 2023. All patients were tested in a single reference laboratory (OC Precision Medicine) and originated from several Brazilian centers within the Oncoclínicas network. Two distinct germline NGS assays were used: breast and ovarian cancer (BOC) panel (36 genes) and a pan-cancer (PC) panel (105 genes). Results: In the overall cohort, 2,651 women with BC were included in this analysis. The median age at genetic testing was 51 years. 1,867 pts (70.4%) underwent a PC panel testing and the remaining 784 pts (29.6%) a BOC panel.Overall, 314 (12%) pts carrier of LP/PV in high- and/or moderate-penetrance genes. Two or more heterozygous LP/PV were found in 35 pts (1.32%), including 8 pts (1.02%) in the BOC panel and 27 pts (1.44%) in the PC panel subgroups. There were no differences in age of onset of BC in single vs co-occurring double mutants. The most frequent co-existing PV/LPV were found in BRCA2 (11) / BRCA1 (8) / PALB2 (4) / TP53 (3) and MUTYH (7) / CHEK2 (3) in the high and moderate penetrance genes, respectively. Six pts (0.23%) had a double heterozygous involving high and/or moderate penetrance genes. Interestingly, there was a case with four heterozygous variants in TP53, MUTYH, MUTYH and APC. Conclusions: In times of rapid incorporation of MGPT in the clinical practice, our real-world data showed that a small proportion of BC patients could be carriers of two or more germline heterozygous LP/PV in cancer genes. However, this represents a challenging scenario for patient and family management, especially in a co-occurrence of high and moderate penetrance genes.

ADAMTSL2 is a potential prognostic biomarker and immunotherapeutic target for colorectal cancer: Bioinformatic analysis and experimental verification.

The ADAMTS Like 2 (ADAMTSL2) mutation has been identified to be associated with different human genetic diseases. The role of ADAMTSL2 is unclear in colorectal cancer (CRC). The study investigated the expression of ADAMTSL2 in both pan cancer and CRC, using data from The Cancer Genome Atlas (TCGA) database to assess its diagnostic value. The study examined the correlation between ADAMTSL2 expression levels and clinical characteristics, as well as prognosis in CRC. The study explored potential regulatory networks involving ADAMTSL2, including its association with immune infiltration, immune checkpoint genes, tumor mutational burden (TMB) / microsatellite instability (MSI), tumor stemness index (mRNAsi), and drug sensitivity in CRC. ADAMTSL2 expression was validated using GSE71187 and quantitative real-time PCR (qRT-PCR). ADAMTSL2 was aberrantly expressed in pan cancer and CRC. An increased level of ADAMTSL2 expression in patients with CRC was significantly associated with the pathologic N stage (p < 0.001), pathologic stage (p < 0.001), age (p < 0.001), histological type (p < 0.001), and neoplasm type (p = 0.001). The high expression of ADAMTSL2 in patients with CRC was found to be significantly associated with a poorer overall survival (OS) (HR: 1.67; 95% CI: 1.18-2.38; p = 0.004), progression-free survival (PFS) (HR: 1.55; 95% CI: 1.14-2.11; p = 0.005) and disease-specific survival (DSS) (HR: 1.83; 95% CI: 1.16-2.89; p = 0.010). The expression of ADAMTSL2 in patients with CRC (p = 0.009) was identified as an independent prognostic determinant. ADAMTSL2 was associated with extracellular matrix receptor (ECM-receptor) interaction, transforming growth factor β (TGF-β) signaling pathway, and more. ADAMTSL2 expression was correlated with immune infiltration, immune checkpoint genes, TMB / MSI and mRNAsi in CRC. ADAMTSL2 expression was significantly and negatively correlated with 1-BET-762, Trametinib, and WZ3105 in CRC. ADAMTSL2 was significantly upregulated in CRC cell lines. The high expression of ADAMTSL2 is significantly correlated with lower OS and immune infiltration of CRC. ADAMTSL2 may be a potential prognostic biomarker and immunotherapeutic target for CRC patients.

CSE1L as a prognostic biomarker associated with pan cancer immune infiltration and drug sensitivity

ABSTRACT Background Rising cancer-related mortality underscores the importance of biomarkers for treatment and prognosis, with Chromosome Segregation 1 Like (CSE1L) linked to various cancers yet its roles remain partially understood. This study investigates CSE1L’s expression and oncogenic mechanisms in solid tumors. Research design and methods We analyzed multi-omics data from 31 solid tumors, measured CSE1L in 41 head and neck carcinoma patients post-chemotherapy via qRT-PCR, and evaluated the impact of CSE1L knockdown on cell proliferation in A549 and HepG2 cells. Results In this study, we observed significantly elevated levels of CSE1L RNA in 13 tumor tissues and protein levels in 8 tumor tissues compared to their corresponding adjacent normal tissues. Additionally, our investigation unveiled a correlation between heightened CSE1L expression in tumor tissues and worsened patient prognosis, poor response to immunotherapy, and diminished effectiveness of neoadjuvant chemotherapy. Through an analysis of CSE1L mechanisms, we discovered its potential involvement in promoting tumor cell proliferation, enhancing drug resistance, and influencing immune infiltration, thereby impacting patient prognosis and treatment outcomes. Finally, we delved into the potential mechanisms underlying upregulation of CSE1L in tumor tissues. Conclusion Our findings demonstrate that CSE1L promotes tumor development in various malignancies, highlighting its potential as both a therapeutic target and prognostic indicator.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks.

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

Topical hidden genome: discovering latent cancer mutational topics using a Bayesian multilevel context-learning approach.

Inferring the cancer-type specificities of ultra-rare, genome-wide somatic mutations is an open problem. Traditional statistical methods cannot handle such data due to their ultra-high dimensionality and extreme data sparsity. To harness information in rare mutations, we have recently proposed a formal multilevel multilogistic "hidden genome" model. Through its hierarchical layers, the model condenses information in ultra-rare mutations through meta-features embodying mutation contexts to characterize cancer types. Consistent, scalable point estimation of the model can incorporate 10s of millions of variants across thousands of tumors and permit impressive prediction and attribution. However, principled statistical inference is infeasible due to the volume, correlation, and noninterpretability of mutation contexts. In this paper, we propose a novel framework that leverages topic models from computational linguistics to effectuate dimension reduction of mutation contexts producing interpretable, decorrelated meta-feature topics. We propose an efficient MCMC algorithm for implementation that permits rigorous full Bayesian inference at a scale that is orders of magnitude beyond the capability of existing out-of-the-box inferential high-dimensional multi-class regression methods and software. Applying our model to the Pan Cancer Analysis of Whole Genomes dataset reveals interesting biological insights including somatic mutational topics associated with UV exposure in skin cancer, aging in colorectal cancer, and strong influence of epigenome organization in liver cancer. Under cross-validation, our model demonstrates highly competitive predictive performance against blackbox methods of random forest and deep learning.

Abstract 864: Pan-cancer analysis of lactic acid metabolism landscape across the Cancer Genome Atlas

Abstract Introduction: Metabolic reprogramming plays an important role in tumor occurrence and progression. Our studies confirmed the survival state of patients with different metabolic systems was heterogeneous and glycolytic metabolism may cause tumor progression. Based on these findings, lactic acid metabolism in glycolysis aroused our interest. This study evaluated the potential association between lactate metabolism gene and tumor clinical process in hepatocellular carcinoma, and proved that it can be used as an effective tool for survival prediction and treatment guidance of 32 kinds of tumor patients by establishing lactate score prognosis model. Methods: We used the expression profile, proteomics and epigenetics of HCC lactate gene set in the Cancer Genome Atlas Database to systematically describe the changes of lactate related genes. The differentially expressed genes were then verified in 32 clinical tumor data sets. A prognostic model of tumor lactic acid infiltration was constructed to evaluate its correlation with the prognosis of patients. Finally, we analyzed the effects of lame score, immunotherapy and drug response on the clinical process of tumor. Results: Firstly, we analyzed the differential expression of lactate metabolism genes in HCC and found that the prognosis of patients with high lactate infiltration was significantly lower than that of mild infiltration. AF angiogenesis factor and EMT factor in high infiltration may be the main reason for their differential expression. We constructed a tumor lactic acid prognosis model through six significantly different lactic acid genes, and found that lame score can be used as a predictor of immunotherapy. In addition, we proved the role of lame score in Pan cancer. PGA was positively correlated with lame score in most tumors. The prognosis of 16 tumors with high lame score group was significantly lower than that of low lame score group. There were significant differences in lame score between metastatic and non metastatic cancer groups of Cesc, kirc and kirp. The high and low risk groups of some tumors showed different dryness indices and dampness. At the same time, methylation gene modification has a significant impact on the Lame score of pan cancer, and the Lame score is used to link the drug tolerance and specific pathway enrichment of pan cancer tumor cell lines, confirming the targeted effect of Lame score on tumor treatment. Finally, we used the clinical characteristics and immunohistochemical analysis of a cohort study of real patients with breast cancer endocrine therapy (Tamoxifen) and hepatocellular carcinoma targeted therapy (Lenvartinib) to verify the clinical treatment prediction ability of lame score. Conclusions: Our study provides a comprehensive analysis of lactate metabolic across cancers and highlights the potential treatment of lactate targeted therapies for cancers. Citation Format: Xiaolin Wei, Lei Cai, Qian He. Pan-cancer analysis of lactic acid metabolism landscape across the Cancer Genome Atlas [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 864.

Abstract 3039: Pan cancer therapeutic inhibition of oncogenic c-MYC by the engineered destabilized 3’UTR of c-MYC

Abstract c-MYC is a master transcription factor that is over expressed in more than 70% of human cancers. There is no clinically approved direct inhibitor of c-MYC. Recently, we reported the development of the engineered destabilized 3’UTR of MYC constructs which is a novel mRNA overwriting technology through which we directly destabilized and degraded c-MYC. Here we report that we have extended this technology in directly targeting and degrading c-MYC in multiple ethnically diverse triple negative breast cancer cell lines, ovarian cancers, neuroendocrine prostate cancers and pancreatic cancers. The constructs are specific, titratable, and directly engaged the c-MYC target validated by RNA transcript technologies. We have performed head-to-head IC50 dose dependent titration comparison with the engineered destabilized 3’UTR of c-MYC constructs and chemotherapies (DNA damaging agents, microtubules inhibiting drugs, alkylating agents) as well as immune checkpoint inhibitor. We found evidence that suggests that the engineered destabilized 3’UTR of c-MYC is likely to be superior to these therapies in pan cancers driven by c-MYC. Citation Format: Chidiebere U. Awah. Pan cancer therapeutic inhibition of oncogenic c-MYC by the engineered destabilized 3’UTR of c-MYC [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 3039.

Abstract 5552: Uncovering clinically significant tumor microenvironment interaction programs across diverse cancers

Abstract Background: Cell-cell interactions (CCI) within the tumor microenvironment (TME) play pivotal roles in various tumor behaviors, including cancer growth, metastasis, immune evasion, and resistance to therapy. Compared to front-line treatments, targeting specific CCIs marks a paradigm shift in cancer therapy, aiming for enhanced response rates with reduced side effects. Although current approaches targeting immune regulation pathways exhibit effective anti-tumor responses, substantial variability in response rates across patients and cancer types persists. Consequently, a critical imperative emerges to discover novel interaction programs (IPs) across diverse TMEs, demonstrating clear clinical impact across a broad spectrum of patients. Methods: Characterization of pan cancer IPs. We compiled a pan cancer single-cell RNA-seq (scRNA-seq) atlas, including 4 million cells from 890 tumors across 14 cancer types. In each sample, CCIs were inferred using a ligand-receptor (LR) analysis framework, generating ranked CCI scores based on consensus from various LR inference methods. To find IPs enriched across TMEs, we applied an unsupervised factorization approach. The outcome represents CCIs as factors, where sample loading indicates factors’ strength, and feature loading highlights the cells and LR pairs constituting each IP. Evaluating IPs in clinical RNA-seq cohorts. Given the more immediate translational potential of bulk cancer sequencing for patient stratification, we devised an approach to predict IPs' strengths in bulk RNA-seq. Random Forest regression models using pseudo-bulk expression of cancer genes were trained to predict the loading (strength) of factors (IPs) in each sample in the scRNA-seq pan-cancer atlas. These models were subsequently applied to cancer samples in The Cancer Genome Atlas (TCGA) cohort to assess the clinical impact of various IPs on patient mortality. Results: We assessed the impact of IPs on 5-year overall survival using Cox proportional hazard models. We identified multiple factors significantly associated with survival in at least 4 cancer types. Notably, a robust prognostic factor linked to the inclusion of anti-tumor natural killer cell interactions and exclusion of pro-tumor macrophage interactions was found in MESO, LGG, ACC, and UVM (HR 1.6-6.6, p &amp;lt; 0.05). The validation of IPs using spatial transcriptomics and evaluation of IP prediction's utility in targeted treatment cohorts are currently underway. Conclusion: We highlight a potent method for detecting clinically significant IPs involving cells in TME communicating through LR pairs. The ability to assess these scRNA-seq-derived IPs in clinical bulk RNA-seq cohorts signifies a valuable advancement. Our approach holds promise for expanding the repertoire of cell therapies, identifying new treatment targets, and improving our predictive capabilities for responses to existing therapies. Citation Format: Ido Nofech-Mozes, Vivian Wang, Philip Awadalla, Sagi Abelson. Uncovering clinically significant tumor microenvironment interaction programs across diverse cancers [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 5552.

Abstract 3034: Krüppel-like factors in regulation of gastric cancer progression

Abstract Introduction: Gastric cancer (GC) is the third leading cause of cancer-associated mortality and the fifth most frequently diagnosed cancer worldwide. The development and progression of GC is a complicated multistage process subjected to dynamic changes in gene regulation. Investigating the effects of these changes is therefore critical for improving our knowledge about GC initiation and progression. Krüppel-like factors (KLFs) are evolutionarily conserved zinc finger-containing transcription factors with altered expressions and diverse regulatory functions in GC. We previously reported that there is loss of KLF4 in GC. Here we report that KLF4 is a crucial regulator of KLF5 expression and vice versa and together they regulate GC cell behavior. Methods: The Cancer Genome Atlas (TCGA) and pan cancer data of differential expressions of KLFs in GC was analyzed. TCGA RNAseq and clinical data for the differential expression status of KLF genes in normal and cancerous tissues and the clinicopathological association was accessed from the UALCAN web portal. The expressions of KLF4 and KLF5 in human normal stomach and GC and orthotopic xenografts were detected by immunohistochemistry (IHC). KLF4, KLF5 cross regulation was evaluated by gene manipulation of each gene individually and checking the expression of the other factor in GC cells. The effect of KLFs on GC cell proliferation, migration, and invasion was determined by Ki67 staining of tissues, PrestoBlue cell viability assay, scratch wound and transwell cell invasion assays. Results and Conclusion: Our results indicated that not only KLF4 and KLF5 have contrasting expressions and effects in GC but also these two factors cross regulate each other. While lower expressions of KLF4 was found in human GC and orthotopic xenografts, increased expression of KLF5 was found in both human GC tissue and orthotopic xenografts. KLF4 silencing and CRISPR/Cas9 knockdown in human GC cells resulted in increased expression of KLF5 which was associated with increased GC cell proliferation and invasiveness. Interestingly, KLF5 knockdown by CRISPR/Cas9 in human GC cells on the other hand resulted in increased expression of KLF4, which was associated with decreased GC cell growth. Our data therefore suggests that the differential expressions of KLF4 and KLF5 might serve as valuable prognostic markers in GC. Citation Format: Sooraj Kakkat, Prabhat Suman, Sandeep Goswami, Sujit Basu, Martin J. Heslin, Elba A. Turbat-Herrera, Veronica Ramirez Alcantara, Chandrani Sarkar, Debanjan Chakroborty. Krüppel-like factors in regulation of gastric cancer progression [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 3034.

Abstract 6843: Comprehensive multi-omics approaches for identification of genetic alterations in head and neck squamous cell carcinoma

Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is one of the most difficult and challenging malignancies, with a high level of heterogeneity and a wide range of treatment responses, regardless of the clinical stage. Oral squamous cell carcinoma (OSCC) is the most common head and neck cancer and accounts for over 90% of cancers that develop in the mucosal epithelium of the oral cavity. Additional carcinogenic risk factors, including tobacco, alcohol, and HPV infection are also associated with the pathogenesis of oral carcinogenesis. Unfortunately, today the failure of standard treatment modalities such as surgery, radiotherapy, and chemotherapy underscore the need for comprehensive genomic profiling to provide a better picture of the genetic alterations and gain an improved understanding of the complex signaling networks involved in the development of potential treatment resistance as well as the identification of novel biomarkers that discriminate between smokers and non-smokers. Methods: A retrospective analysis was performed on biopsied Formalin-Fixed Paraffin-Embedded (FFPE) samples from OSCC patients with and without a history of smoking and treated +/- chemotherapy. Patient samples representing matched normal tissue to serve as controls were compared to tumor squamous cell carcinoma samples and profiled using a single assay panel that includes 517 genes by both DNA and RNA NGS, microsatellite instability (MSI), and tumor mutational burden (TMB). Further analysis was also performed using the NanoString nCounter® PanCancer Immune Profiling Panel (PCIP), 770-comprehensive gene expression panel Results: The Neo ComprehensiveTM Solid Tumor pan cancer assay enabled simultaneously analysis of both DNA and RNA in one integrated workflow with an accompanying DragenTM bioinformatics analysis platform and provided comprehensive genomic profiling of sequence and structural variants, as well as genomic signatures such as TMB and MSI in OSCC patients. Utility of the NanoString PCIP highlighted immune-relevant gene expression changes within the different sample cohorts. The detailed molecular information highlighted by our study emphasizes the need for improved patient classification based on smoking status in the management of OSCC and also in establishing potential therapeutic options based on the many altered cell signaling pathways that we identified. By combining a multi-omics approach with expression data for immune-related genes and associated overall survival data, we provide an effective strategy and workflow for the identification of prognostic biomarkers in OSCC. Citation Format: Kirsteen Maclean, Qinqin Zha, Lakshmi Chandramohan, Anna Juncker-Jensen. Comprehensive multi-omics approaches for identification of genetic alterations in head and neck 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 6843.

Abstract 114: Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu)

Abstract Our goal is to identify, in situ, the regulatory genes that dictate the onset age and growth rate of spontaneously arising tumors to implement new intervention strategies. For genetic linkage analysis, we crossed HER2(neu) Tg mice with Diversity Outbred (DO) mice, an outbred population comprised of 8 founding strains (A/J, C57BL/6J, 129S1/SvlmJ, NOD/ShiLtJ, NZO/HILtJ, CAST/EiJ, PWK/PhJ, WSB/EiJ) maintained by non-sibling crossing to ensure each mouse is genetically unique. Using R/QTL package, we linked Quantitative Trait Loci (QTL) in Chr 1 and X with tumor onset age, and a Chr 10 QTL with tumor growth rate. The Chr1 (=human Chr2) QTL was linked to human breast cancer diagnosis in 11 Genome-Wide Association Studies (GWAS; the human GWAS catalog, https://www.ebi.ac.uk/gwas/). Because human GWAS data is deficient in Chr X mapping and also does not assess tumor growth rate as a trait, the QTL loci identified in mouse Chr X and 10 were discoveries beyond the capacity of human GWAS. In total, we identified 26 candidate genes across the 3 QTL. For clinical validation, the genes were analyzed with CodeAI (Caris LS) which associated cancer patient clinical data with candidate gene expression. We found 21/26 genes significantly associated with the survival of patients with primary (n=3,533) and/or metastatic (n=4,870) breast cancers and 17/26 were associated with lung cancer (n=11,334) survival, with 13 overlapping genes between lung and breast cancer, indicating broad applicability of these candidate genes. We interrogated the immune status in BALB NeuT and (BALBxPWK)F1 NeuT mice because the F1 mice developed tumors around 9 wk, much earlier than the 14 wk observed in BALB NeuT mice. Surprisingly, (BALBxPWK)F1 mice responded to cancer vaccines more vigorously. Single cell RNA (scRNA) libraries from (BALBxPWK)F1 NeuT tumors showed an expanded lymphocyte cluster (12%), compared with BALB NeuT (2%) and an enrichment of T cell activation genes. These findings may reflect a deficiency in tumor cell recognition by the activated anti-tumor effectors and a window of opportunity for correction. Of the 21 candidate genes, LILRB4, a myeloid cell checkpoint molecule, was of particular interest. Expression of LILRB4 is predictive of patient survival in both breast and lung cancer. Using scRNA sequencing, we found this transmembrane receptor expressed primarily by tumor infiltrating myeloid cells. In a reported scRNA sequencing dataset (GSE161529), LILRB4 was expressed by infiltrating macrophages in human breast cancers, and is also correlated with reduced survival. In a PAN Cancer ATACseq dataset (Corces et al., 2018), promoter accessibility of LILRB4 was associated with reduced survival. Taken together, there are multiple immune regulatory mechanisms of tumor progression and LILRB4 is an important new actionable target. CA76340 (WZW), KCI TBM program (JBJ) and CCSG P30 CA022453 (GB). Citation Format: Jennifer B. Jacob, Wei-Zen Wei, Benjamin L. Kidder, Tolulope Adeyelu, Andrew Elliott, Gerold Bepler, Joyce D. Reyes. Identification of the actionable target, LILRB4, through genetic linkage analysis of Diversity Outbred (DO) F1 mice expressing HER2(neu) [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 114.

Abstract 988: Genome-wide repeat landscapes in cancer and cell-free DNA

Abstract Introduction: Repeat sequences comprise &amp;gt;50% of the human genome and structural and epigenetic changes in these regions are implicated in cancer. However, no systematic analysis of the compendium of repeat sequences has ever been performed in human cancer or cell-free DNA (cfDNA), largely due to the inability to identify and quantify repeat sequences genome-wide. We describe here the first comprehensive analysis of genome-wide repeat landscapes in cancer and demonstrate their utility in cfDNA liquid biopsies. Methods: We developed ARTEMIS (Analysis of RepeaT EleMents in dISease) an alignment-free, genome-wide approach for analyzing repeat landscapes in short read sequencing. This approach uses a de novo search of short sequences (kmers) in the telomere to telomere (chm13) reference genome to identify 1.2 billion 24-mers uniquely defining 1280 individual repeat types occurring genome-wide across 57 subfamilies and 6 families. We analyzed ARTEMIS kmers in whole genome sequences of 525 matched tumor/normal pairs from breast, colorectal, liver, lung, ovarian, cervical, prostate, thyroid, head and neck, gastric, and bladder cancers in the Pan Cancer Analysis of Whole Genomes (PCAWG), and in low coverage (1-2x) whole genome sequences of 1450 cfDNA samples from individuals with and without 8 types of cancer. Results: Analysis of ARTEMIS kmer repeat landscapes in 525 PCAWG tumors identified changes in all 1280 repeat element types, including 820 novel elements not previously known to be altered in cancer. A median of 807 repeat elements (range 246-1280) were altered in each tumor compared to its matched normal. The majority of changes were in repeat elements not previously described as altered in tumorigenesis and were most frequently found within Satellites, LINEs and SINEs, though changes were also observed in LTRs, Transposable Elements, and RNA Elements. A cross-validated cfDNA model using repeat landscapes (ARTEMIS) and fragmentation features (DELFI) detected individuals in a diagnostic cohort (n=287) across all stages of lung cancer with high performance (AUC 0.91, 95% CI 0.88-0.95) and was externally validated in a separate population (n=513). The locked model generated scores that correlated with circulating tumor mutant allele fractions for patients (n=19) undergoing targeted lung cancer therapy (r=0.80, p&amp;lt;2.2e-16), and stratified progression-free survival (p&amp;lt;0.001). ARTEMIS repeat landscape analyses of cfDNA also detected liver cancer in a high-risk cohort (n=208) of individuals with cirrhosis or viral hepatitis (AUC 0.91, 95% CI 0.87-0.95), and identified tissue of origin among seven tumor types (n=423). Conclusions: ARTEMIS reveals genome-wide repeat landscapes in human cancer, including in 820 novel elements not previously known to be altered in tumorigenesis. These repeat landscapes that can now be described are evaluable in the circulation and provide an avenue for noninvasive detection and characterization of cancer. Citation Format: Akshaya Annapragada, Noushin Niknafs, James R. White, Daniel C. Bruhm, Christopher Cherry, Jamie E. Medina, Vilmos Adleff, Carolyn Hruban, Dimitrios Mathios, Zachariah H. Foda, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. Genome-wide repeat landscapes in cancer and cell-free DNA [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 988.

Panel Comparative Analysis Tool: An Open-Source Comparative Analysis Tool for Next-Generation Sequencing Panel Target Regions

Multi-gene next-generation sequencing (NGS) panels have become a routine diagnostic method in the contemporary practice of personalized medicine. To avoid inadequate test choice or interpretation, a detailed understanding of the precise panel target regions is required. However, the necessary bioinformatic expertise is not always available, and publicly accessible and easily interpretable analyses of target regions are scarce. To address this critical knowledge gap, we present the Panel Comparative Analysis Tool (PanelCAT) an open-source application to analyze, visualize and compare NGS panel DNA target regions. PanelCAT uses RefSeq, ClinVar and COSMIC cancer mutation census databases to quantify the exon and mutation coverage of target regions and provides interactive graphical representations and search functions to inspect the results. We demonstrate the utility of PanelCAT by analyzing two large NGS panels (Illumina TruSight Oncology 500, and Qiagen Human Pan Cancer Panel) to validate the advertised target genes, quantify targeted exons and mutations, and identify differences between panels. PanelCAT will enable institutions and researchers to catalogue and visualize NGS panel target regions independent of the manufacturer, promote transparency of panel limitations, and share this information with employees and requisitioners.

Identification of ALYREF in pan cancer as a novel cancer prognostic biomarker and potential regulatory mechanism in gastric cancer

ALYREF is considered as a specific mRNA m5C-binding protein which recognizes m5C sites in RNA and facilitates the export of RNA from the nucleus to the cytoplasm. Expressed in various tissues and highly involved in the transcriptional regulation, ALYREF has the potential to become a novel diagnostic marker and therapeutic target for cancer patients. However, few studies focused on its function during carcinogenesis and progress. In order to explore the role of ALYREF on tumorigenesis, TCGA and GTEx databases were used to investigate the relationship of ALYREF to pan-cancer. We found that ALYREF was highly expressed in majority of cancer types and that elevated expression level was positively associated with poor prognosis in many cancers. GO and KEGG analysis showed that ALYREF to be essential in regulating the cell cycle and gene mismatch repair in tumor progression. The correlation analysis of tumor heterogeneity indicated that ALYREF could be specially correlated to the tumor stemness in stomach adenocarcinoma (STAD). Furthermore, we investigate the potential function of ALYREF on gastric carcinogenesis. Prognostic analysis of different molecular subtypes of gastric cancer (GC) unfolded that high ALYREF expression leads to poor prognosis in certain subtypes of GC. Finally, enrichment analysis revealed that ALYREF-related genes possess the function of regulating cell cycle and apoptosis that cause further influences in GC tumor progression. For further verification, we knocked down the expression of ALYREF by siRNA in GC cell line AGS. Knockdown of ALYREF distinctly contributed to inhibition of GC cell proliferation. Moreover, it is observed that knocked-down of ALYREF induced AGS cells arrested in G1 phase and increased cell apoptosis. Our findings highlighted the essential function of ALYREF in tumorigenesis and revealed the specific contribution of ALYREF to gastric carcinogenesis through pan-cancer analysis and biological experiments.

Cirrhotic-extracellular matrix attenuates aPD-1 treatment response by initiating immunosuppressive neutrophil extracellular traps formation in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is closely associatedwith chronic liver diseases, particularly liver cirrhosis, which has an altered extracellular matrix (ECM) composition. The influence and its mechanism of the cirrhotic-ECM on the response of HCC to immune checkpoint inhibitor (ICI) remains less clarified.MethodsIn silico, proteomic and pathological assessment of alteration of cirrhotic-ECM were applied in clinical cohort. Multiple pre-clinical models with ECM manipulation were used to evaluate cirrhotic-ECM’s effect on ICI treatment. In silico, flow cytometry and IHC were applied to explore how cirrhotic-ECM affect HCC microenvironment. In vitro and in vivo experiments were carried out to identify the mechanism of how cirrhotic-ECM undermined ICI treatment.ResultsWe defined “a pro-tumor cirrhotic-ECM” which was featured as the up-regulation of collagen type 1 (Col1). Cirrhotic-ECM/Col1 was closely related to impaired T cell function and limited anti PD-1 (aPD-1) response of HCC patients from the TCGA pan cancer cohort and the authors’ institution, as well as in multiple pre-clinical models. Mechanically, cirrhotic-ECM/Col1 orchestrated an immunosuppressive microenvironment (TME) by triggering Col1-DDR1-NFκB-CXCL8 axis, which initiated neutrophil extracellular traps (NETs) formation to shield HCC cells from attacking T cells and impede approaching T cells. Nilotinib, an inhibitor of DDR1, reversed the neutrophils/NETs dominant TME and efficiently enhanced the response of HCC to aPD-1.ConclusionsCirrhotic-ECM modulated a NETs enriched TME in HCC, produced an immune suppressive TME and weakened ICI efficiency. Col1 receptor DDR1 could be a potential target synergically used with ICI to overcome ECM mediated ICI resistance. These provide a mechanical insight and novel strategy to overcome the ICI resistance of HCC.