Cancer Genome Research Articles

FTH1P8 induces and transmits docetaxel resistance by inhibiting ferroptosis in prostate cancer

Overcoming docetaxel resistance remains a significant challenge in the management of prostate cancer. Previous studies have confirmed a link between ferroptosis and the development of docetaxel resistance. This study revealed that docetaxel-resistant prostate cancer cells presented increased FTH1P8 expression compared with docetaxel-sensitive cells. Decreasing the level of FTH1P8 counteracted docetaxel resistance and facilitated docetaxel-induced ferroptosis, which is characterized by an increase in intracellular Fe2+ concentration, lipid peroxidation levels (lipid ROS), reactive oxygen species (ROS) accumulation, malondialdehyde (MDA) production and mitochondrial damage, a decrease in the Fe3+ concentration and glutathione (GSH) content, and the ability to inhibit hydroxyl radical (·OH) and the mitochondrial membrane potential (MMP). Conversely, increasing the level of FTH1P8 had the opposite effect. A positive correlation was revealed between the expression of FTH1P8 and its parental gene FTH1 in prostate cancer tissues in The Cancer Genome Atlas (TCGA) database. Molecular investigations revealed that FTH1P8 expression increased through miR-1252-5p. Furthermore, rescue experiments confirmed that FTH1 mediated the inhibitory effect of FTH1P8 on ferroptosis. Moreover, FTH1P8 was discovered to play a role in the spread of docetaxel resistance via exosomes. Docetaxel-siRNA targeting FTH1P8 (siFTH1P8)-nanoliposomes (DOC-siFTH1P8-LIP), which can codeliver docetaxel and siFTH1P8, significantly inhibited docetaxel resistance in cells. These results indicated that FTH1P8 can function as both an indicator and a treatment target for docetaxel resistance. The use of DOC-siFTH1P8-LIP demonstrated promising therapeutic effects on docetaxel-resistant cells, suggesting a novel option for treating docetaxel-resistant prostate cancer.

Association of COL4A2 indel polymorphism with the development of stomach adenocarcinoma in Chinese populations

Objective The objective of the study was to assess the potential association between the indel polymorphism (rs34802628) located within the intron of the collagen type ⅳ alpha 2 gene (COL4A2) and the susceptibility to stomach adenocarcinoma (STAD) within a Chinese population. Methods Peripheral venous blood samples were collected from a total of 497 STAD patients and 804 healthy control individuals to extract genomic DNA. The genotyping of the COL4A2 rs34802628 polymorphism was carried out using a polymerase chain reaction assay. Additionally, statistical analyses were conducted on the expression levels of COL4A2 mRNA using the GEPIA database. Meanwhile, the expression of COL4A2 mRNA was also validated by Real-time PCR using STAD tissue samples. Then, based on an analysis of patient tumor RNA seq data available from the Cancer Genome Atlas (TCGA), we assessed the prognostic value of mRNA expression of the COL4A2 gene in STAD patients using K–M plotter. Results The study presented compelling evidence supporting an association between the rs34802628 polymorphism in the COL4A2 gene and susceptibility to STAD. Logistic regression analysis revealed that both the heterozygote and homozygote 4-bp del/del genotypes were significantly associated with a decreased risk of STAD, even after controlling for other variables (adjusted odds ratio [OR] = 0.663, 95% confidence interval [CI] 0.519–0.848, p = 0.037; OR = 0.422, 95% CI 0.290–0.614, p = 0.000005, respectively). Importantly, individuals carrying the 4-bp deletion allele demonstrated a notably lower risk of developing the disease (OR = 0.696, 95% CI 0.591–0.820, p = 0.000014). Furthermore, Genotype-phenotype correlation studies in human STAD tissue samples demonstrated that the higher mRNA expression levels of COL4A2 were associated with the ins allele of rs34802628. Bioinformatics analysis revealed that higher expression of the COL4A2 gene was significant with development and poor prognosis of STAD. Conclusion The results of our study provide strong evidence indicating a potential involvement of genetic variants in the COL4A2 gene in the development of STAD. Nonetheless, to validate and consolidate these findings, additional investigations incorporating larger sample sizes and functional experiments are necessary.

Prediction of the 3D cancer genome from whole-genome sequencing using InfoHiC.

The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC , uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets.

A Graph-Informed Modeling Framework Empowering Gene Pathway Discovery.

This study introduces a novel graph-informed modeling framework for improving the statistical analysis of gene expression data, particularly in the context of identifying differentially expressed gene pathways and gene expression-assisted disease classification in a high-dimensional data setting. By integrating gene regulatory network information into hypothesis testing for the difference between mean vectors and linear discriminant analysis, we aim to effectively capture and utilize previously validated external gene interaction information. Our method leverages a block-coordinate descent approach which enables us to incorporate mixed graph information into linear structural equation modeling, accommodating directed/undirected edges and potential cycles in gene regulatory networks. Extensive simulations under various data scenarios have demonstrated the effectiveness of our approach with improved power for gene pathway tests and disease classification over existing methods. An application to a lung cancer dataset from the Cancer Genome Atlas Program (TCGA) further exemplifies the potential of our graph-informed approach in empowering the detection of differentially expressed gene pathways and gene expression-based classification of different lung cancer stages. Our findings underscore the potential utility of incorporating gene regulatory network information in gene pathway analysis, setting the stage for future advancements in gene pathway discovery, disease diagnosis, and treatment strategies.

Long non-coding RNA FAM87A is associated with overall survival and promotes cell migration and invasion in gastric cancer.

The role of long non-coding RNAs (lncRNAs) in the invasion and metastasis of gastric cancer remains largely unclear. Integrating transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differentially expressed genes were identified in gastric cancer. Using the Catalogue of Somatic Mutations in Cancer (COSMIC) database-curated gene set, lncRNAs associated with invasion and metastasis were identified. The Cox analyses were performed to identify prognostic lncRNAs. The competing endogenous RNA (ceRNA) regulation network was constructed to identify hub lncRNAs in gastric cancer. Functional and pathway analyses were used to investigate the function of identified lncRNAs. RT-qPCR and Transwell assays were used to investigate the expression in gastric cancer tissues and functions in gastric cancer cell lines. Based on GEO and TCGA databases, 111 differentially expressed lncRNAs were identified between gastric cancer and normal samples. A total of 43 lncRNAs were significantly correlated with hallmark genes of cancer invasion and metastasis. Among them, as a hub lncRNA in the invasion-related ceRNA regulation network, FAM87A showed potential regulation on MAPK signaling and transforming growth factor (TGF) signaling cascade, such as TGFB2, TGFBR1, and TGFBR2. Furthermore, FAM87A also showed a significant correlation with cell adhesion molecules, such as Integrin alpha 6 (ITGA6) and Contactin-1 (CNTN1). RT-qPCR experiments showed that FAM87A expression was upregulated in gastric cancer tissues compared to normal samples (n = 30). Transwell assays showed that FAM87A knockdown inhibited the migration and invasion abilities of gastric cancer cells in vitro. Notably, clinical data analysis showed that lncRNA FAM87A could be an independent factor for the overall survival of patients with gastric cancer. LncRNA FAM87A may play a pivotal role in regulating migration and invasion of gastric cancer cells. FAM87A could be a potential biomarker for the overall survival of patients with gastric cancer.

CT45A1-mediated MLC2 (MYL9) phosphorylation promotes natural killer cell resistance and outer cell fate in a cell-in-cell structure, potentiating the progression of microsatellite instability-high colorectal cancer.

Patients with microsatellite instability-high (MSI-H) colorectal cancer (CRC) have high tumor mutation burden and tumor immunogenicity, exhibiting a higher response rate to immunotherapy and better survival. However, a portion of MSI-H CRC patients still experience adverse disease outcomes. We aimed to identify the tumor-autonomous regulators determining these heterogeneous clinical outcomes. The Cancer Genome Atlas (TCGA) dataset was used to identify regulators in MSI-H CRC patients with unfavorable outcomes. Stable CRC tumor clones expressing targeted regulators were established to evaluate migratory and stemness properties, immune cell vulnerability, and cell-in-cell (CIC) structure formation. RNA-sequencing (RNA-seq) was used to identify enriched biological pathways in stable CRC tumor clones. Clinicopathological characterization of formalin-fixed paraffin-embedded (FFPE) MSI-H CRC specimens was performed to explore the underlying mechanisms involved. We showed that cancer/testis antigen family 45 member A1 (CT45A1) expression was upregulated in MSI-H CRC patients with poor survival outcomes. CT45A1-expressing microsatellite stable (MSS) CRC cells showed enhanced migratory ability. However, CT45A1-expressing MSI-H CRC cells, but not MSS CRC cells, showed higher resistance to natural killer (NK) cell cytotoxicity and served as outer cells in homotypic CIC structures, preventing exogenous or therapeutic antibody access to inner CRCcells. Inactivating RHO-ROCK/MLCK-MLC2 signaling with small-molecule inhibitors or short-hairpin RNAs (shRNAs) targeting myosin light chain kinase (MYLK) abolished NK cell resistance and reduced the outer cell fate of CT45A1-expressing MSI-H CRC cells. In MSI-H CRC patients, CT45A1-positive tumors exhibited increased MLC2 phosphorylation, increased outer cell fate, and decreased survival. We demonstrated that CT45A1 potentiates the advanced progression of MSI-H CRC, and targeting MLC2 phosphorylation may enhance immunotherapy efficacy in CT45A1-positive MSI-H CRC patients.

Pyroptosis-related genes features on prediction of the prognosis in liver cancer: An integrated analysis of bulk and single-cell RNA sequencing

ObjectiveThis study explores the impact of pyroptosis-related genes (PRG) on the prognosis of liver cancer (LC). Methods421 samples (371 tumor samples and 50 normal samples) from the Cancer Genome Atlas (TCGA) were included in this study. GSE14520 dataset (data of RNA expression and relevant clinicopathological features), GSE125449 dataset (single-cell data in LC) and HCCDB18 dataset (validation on the reliability of the model) were downloaded as appropriate. Download the PRG and its corresponding pathway information from the gene set enrichment analysis (GSEA) website. The consensus clustering was performed by ConsensusClusterPlus package. Differentially expressed genes (DEGs) were identified using limma package, and prognostic features were constructed using un/multivariate and Lasso Cox regression. Pathway enrichment analysis was conducted by ssGSEA method. Receiver Operating Characteristic and the survival analysis were conducted by timeROC and Survminer packages. The Seurat package was used for single-cell RNA sequencing (scRNA-seq) analysis. For cellular validation, following the quantification on the key genes via reverse-transcription quantitative PCR, the Transwell and scratch assays were applied to evaluate the in-vitro invasion and migration of LC cells Huh-7. Results12 prognosis-related genes were identified to be related to the progression of LC. Three subtypes including C1, C2 and C3 were categorized using the 12 prognosis-related genes and PRGs significantly related to the prognosis of LC patients. The worst and best prognosis was seen in C3 subtype and C2 subtype, respectively. Hallmark pathway enrichment analysis has shown the concurrent immunoactivation and immune escape in C3 subtype. A RiskScore model was constructed using 8 key genes (KPNA2, UCK2, FTCD, CBX2, RAB32, HMMR, S100A9 and ANXA10) from the DEGs of three subtypes. The RiskScore system as an independent prognostic factor dividing the patients into high and low risk groups, and patients of the high-risk group had poor prognosis in both test set and validation set. A nomogram model combining the risk score had the extreme higher benefit. Further, 6 subclusters were identified from scRNA-seq analysis, where the highest PYROPTOSIS score was seen in Monocytic-Macrophages. The quantification on the key genes has suggested the high expressions of KPNA2, UCK2, CBX2, RAB32, HMMR and S100A9 and the low expressions of FTCD and ANXA10 in LC cells Huh-7. Particularly, UCK2 knockdown evidently diminished the number of invaded and migrated LC cells in vitro. ConclusionThe risk model associated with pyproptosis is crucial for the tumor immunity of LC and may serve as a prognostic indicator for patients suffering from LC. Our findings will offer new perspectives for immunotherapies targeting LC.

Real-world genome profiling in Japanese patients with pancreatic ductal adenocarcinoma focusing on HRD implications.

Pancreatic ductal adenocarcinoma (PDAC) poses significant challenges due to its high mortality, making it a critical area of research. This retrospective observational study aimed to analyze real-world data from comprehensive genome profiling (CGP) of Japanese patients with PDAC, mainly focusing on differences in gene detection rates among panels and the implications for homologous recombination deficiency (HRD) status. This study enrolled 2568 patients with PDAC who had undergone CGP between June 2019 and December 2021 using data from the nationwide Center for Cancer Genomics and Advanced Therapeutics database. Two types of CGP assays (tissue and liquid biopsies) were compared and a higher detection rate of genetic abnormalities in tissue specimens was revealed. HRD-related gene alterations were detected in 23% of patients, with BRCA1/2 mutations accounting for 0.9% and 2.9% of patients, respectively. Treatment outcome analysis indicated that patients with BRCA1/2 mutations had a longer time to treatment discontinuation with FOLFIRINOX than gemcitabine plus nab-paclitaxel as first-line therapy (9.3 vs. 5.6 months, p = 0.028). However, no significant differences were observed in the treatment response among the other HRD-related genes. Logistic regression analysis identified younger age and family history of breast, prostate, and ovarian cancers as predictive factors for HRD-related gene alterations. Despite the lack of progression-free survival data and the inability to discriminate between germline and somatic mutations, this study provides valuable insights into the clinical implications of CGP in Japanese patients with PDAC. Further research is warranted to optimize panel selection and elucidate the efficacy of platinum-based therapies depending on the HRD status.

The role of pyroptosis-related genes in breast cancer progression

Breast cancer (BC) is one of the most common malignant cancers affecting females worldwide. Pyroptosis, a form of programmed cell death associated with inflammation and triggered by pro-inflammatory signals, is not well understood in the context of BC. This study aimed to investigate the role of pyroptosis in BC patients. Paired tumor and adjacent normal tissue samples were obtained from The Cancer Genome Atlas. Using a least absolute shrinkage and selection operator Cox analysis, we identified 15 prognostic genes associated with BC. Among these, fibrinogen C domain-containing 1, calcium voltage-gated channel subunit alpha1 H, heat shock protein family B (small) member 8, and peroxidasin-like (PXDNL) were classified as high-risk genes in BC. In contrast, the remaining 11 genes, such as proteasome activator subunit 2 and DIRAS (DIRAS family GTPase 3), were low-risk genes. Kyoto Encyclopedia of Genes and Genomes and Gene ontology analyses revealed that immune-related genes were enriched but showed reduced immunological status in the high-risk group, indicating that pro-inflammatory factors and immune antigens were produced during cell death. Consequently, targeting immune antigens with new immunosuppressants may offer a novel approach to treating BC. Moreover, the expression levels of the prognostic genes PXDNL, armadillo-like helical domain-containing 1 (ARMH1), APOBEC3D, and APOBEC3F in BC cell lines were assessed using quantitative polymerase chain reaction and western blotting. PXDNL and ARMH1 exhibited high levels of expression in BC, suggesting they could be potential therapeutic targets.

Pangenome-Informed Language Models for Privacy-Preserving Synthetic Genome Sequence Generation.

The public availability of genome datasets, such as The Human Genome Project (HGP), The 1000 Genomes Project, The Cancer Genome Atlas, and the International HapMap Project, has significantly advanced scientific research and medical understanding. Here our goal is to share such genomic information for downstream analysis while protecting the privacy of individuals through Differential Privacy (DP). We introduce synthetic DNA data generation based on pangenomes in combination with Pretrained-Language Models (PTLMs). We introduce two novel tokenization schemes based on pangenome graphs to enhance the modeling of DNA. We evaluated these tokenization methods, and compared them with classical single nucleotide and k -mer tokenizations. We find k -mer tokenization schemes, indicating that our tokenization schemes boost the model's performance consistency with long effective context length (covering longer sequences with the same number of tokens). Additionally, we propose a method to utilize the pangenome graph and make it comply with DP privacy standards. We assess the performance of DP training on the quality of generated sequences with discussion of the trade-offs between privacy and model accuracy. The source code for our work will be published under a free and open source license soon.

Cell Migration–Proliferation Dichotomy in Cancer: Biological Fact or Experimental Artefact?

The migration–proliferation dichotomy (MPD) has long been observed in cultured cancer cells. This phenomenon is not only relevant to tumour progression but may also have therapeutic significance in clinical cancer. However, MPD has rarely been investigated in primary cancer. This study aimed to either confirm or disprove the existence of MPD in primary cancer. Using primary gastric, colorectal and prostate cancer (GC, CRC and PCa) cohorts from the Cancer Genome Atlas and Memorial Sloan Kettering Cancer Center, this study interrogated the MPD phenomenon by utilising RNA–Seq-based proliferation (CIN70 signature) and migration (epithelial-mesenchymal transition) indices, as well as gene set enrichment analyses (GSEA). Alternative hypothetical migration–proliferation models—The simultaneous migration–proliferation (SMP) and phenotype–refractory (PR) models—were compared to the MPD model by probing the migration–proliferation relationships within cancer stages and between early- and late-stage diseases using chi-square and independent T tests, z-score statistics and GSEA. The results revealed an inverse relationship between migration and proliferation signatures overall in the GC, CRC and PCa cohorts, as well as in early- and late-stage diseases. Additionally, a shift in proliferation- to migration dominance was observed from early- to late-stage diseases in the GC and CRC cohorts but not in the PCa cohorts, which showed enhanced proliferation dominance in metastatic tumours compared to primary cancers. The above features exhibited by the cancer cohorts are in keeping with the MPD model of the migration–proliferation relationship at the cellular level and exclude the SMP and PR migration–proliferation models.

Construction of an endoplasmic reticulum stress and cuproptosis -related lncRNAs signature in chemosensitivity in hepatocellular carcinoma by comprehensive bioinformatics analysis

Endoplasmic reticulum stress (ERS) and cuproptosis have remarkable effects on hepatocellular carcinoma (HCC) leading to a poor prognosis. The current study aimed to explore credible signature for predicting the prognosis of HCC based on ERS and cuproptosis-related lncRNAs. In our study, clinical and transcriptomic profiles of HCC patients were obtained from the Cancer Genome Atlas (TCGA) database. An ERS and cuproptosis-related lncRNA prognostic signature, including NRAV, SNHG3, LINC00839 and AC004687.1, was determined by correlation tests, Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) methods. Survival and predictive value were evaluated using Kaplan–Meier and receiver operating characteristic (ROC) curves, while calibration and nomograms curves were developed. Besides the enrichment analyses for ERS and cuproptosis-related lncRNAs, mutational status and immune status were assessed with TMB and ESTIMATE. Additionally, consensus cluster analysis was employed to compare cancer subtype differences, while drug sensitivity and immunologic efficacy were evaluated for further exploration. qRT-PCR and CCK-8 were utilized to verify the alteration of the prognostic lncRNAs expression and proliferation in vitro. High-risk groups exhibited poorer prognosis. The signature exhibited robust predictive value as an independent prognostic indicator and showed significant correlation with clinicopathological features. In the enriched analysis, biological membrane pathways were enriched. Low-risk patients had lower TMB and higher immune status. A cluster analysis revealed that cluster 2 had the best clinical immunological efficacy and most active immune function. In brief, our constructed signature with ERS and cuproptosis-related lncRNAs was associated survival outcomes of HCC, and can be used to predict the clinical classification and curative effect.

Comprehensive analysis of NOTCH pathway with tumor environment in pancreatic adenocarcinoma

Abstract Objectives Pancreatic adenocarcinoma (PAAD) ranks among the most prevalent malignant neoplasms, and multiple pathways are involved in its pathogenesis, including the NOTCH pathway. However, the variable biological functions of the pathway in PAAD are controversial. Methods RNA-seq data for PAAD was analyzed using data from The Cancer Genome Atlas and Genotype-Tissue Expression databases. Utilizing Kaplan-Meier survival curves and Cox regression analyses, we examined the prognostic significance. The tumor microenvironment and immunotherapy responses were investigated using ssGSEA, ESTIMATE, and TIDE models. Functional enrichment analysis was used to explore gene functions. Results We identified NOTCH2, JAG1, NOTCH4, and DLL3 as high-priority members of the NOTCH pathway that modulates PAAD. Elevated NOTCH2 and JAG1 levels were markedly linked to reduced overall survival (OS), while increased NOTCH4 and DLL3 levels were significantly related to extended OS. Immune analyses showed that NOTCH-based scores were closely related to the immune microenvironment. NOTCH scores were not only closely correlated with tumor-infiltrating immune cells, but also with immunologically activated and immune checkpoint gene expression. The high NOTCH score group had a higher proportion of tumor-infiltrating immune cells and had better responses to immune checkpoint inhibitor therapy. Conclusions These data indicate that NOTCH2, JAG1, NOTCH4, and DLL3 could function as efficient prognostic biomarkers and therapeutic targets in PAAD, and patients with a high NOTCH score may have a significant response to immune checkpoint inhibitor treatment.

A comprehensive in silico analysis and experimental validation of miRNAs capable of discriminating between lung adenocarcinoma and squamous cell carcinoma.

Accurate differentiation between lung adenocarcinoma (AC) and lung squamous cell carcinoma (SCC) is crucial owing to their distinct therapeutic approaches. MicroRNAs (miRNAs) exhibit variable expression across subtypes, making them promising biomarkers for discrimination. This study aimed to identify miRNAs with robust discriminatory potential between AC and SCC and elucidate their clinical significance. MiRNA expression profiles for AC and SCC patients were obtained from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and supervised machine learning methods (Support Vector Machine, Decision trees and Naïve Bayes) were employed. Clinical significance was assessed through receiver operating characteristic (ROC) curve analysis, survival analysis, and correlation with clinicopathological features. Validation was conducted using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, signaling pathway and gene ontology enrichment analyses were conducted to unveil biological functions. Five miRNAs (miR-205-3p, miR-205-5p, miR-944, miR-375 and miR-326) emerged as potential discriminative markers. The combination of miR-944 and miR-326 yielded an impressive area under the curve of 0.985. RT-qPCR validation confirmed their biomarker potential. miR-326 and miR-375 were identified as prognostic factors in AC, while miR-326 and miR-944 correlated significantly with survival outcomes in SCC. Additionally, exploration of signaling pathways implicated their involvement in key pathways including PI3K-Akt, MAPK, FoxO, and Ras. This study enhances our understanding of miRNAs as discriminative markers between AC and SCC, shedding light on their role as prognostic indicators and their association with clinicopathological characteristics. Moreover, it highlights their potential involvement in signaling pathways crucial in non-small cell lung cancer pathogenesis.

MIR4435-2HG: A novel biomarker for triple-negative breast cancer diagnosis and prognosis, activating cancer-associated fibroblasts and driving tumor invasion through EMT associated with JNK/c-Jun and p38 MAPK signaling pathway activation

BackgroundBreast cancer has the highest incidence rate and causes the most fatalities among all female cancers worldwide. Triple-negative breast cancer (TNBC) is known for its strong invasiveness and higher rates of recurrence. In this research, we aimed to identify MIR4435-2HG as a promising long non-coding RNA (lncRNA) biomarker and therapeutic target for TNBC. MethodsUtilizing clinicopathological information and transcriptome data from The Cancer Genome Atlas (TCGA) database, we assessed the clinical relevance of MIR4435-2HG in breast cancer through univariate and multivariate COX regression, receiver operating characteristic (ROC) analysis, as well as Kaplan-Meier survival analysis. To investigate the biological role of MIR4435-2HG in TNBC, we conducted gene set enrichment analysis (GSEA), as well as Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Additionally, we constructed and validated a nomogram to predict disease-free survival (DFS). Both the R package “pRRophetic” and the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were employed to forecast the sensitivity to different therapeutics between the high- and low-MIR4435-2HG groups. We employed single-cell RNA sequencing analysis and tumor microenvironment infiltration analysis to investigate the potential involvement of MIR4435-2HG in the TNBC tumor microenvironment. Cellular biological behaviors were assessed utilizing CCK-8, transwell assays, and wound-healing assays. Furthermore, we performed RNA-seq, qRT-PCR, and western blotting analyses to elucidate and confirm the specific mechanisms underlying the role of MIR4435-2HG in TNBC. ResultsIn our study, we have identified MIR4435-2HG as a significant diagnostic and prognostic factor for TNBC. We observed that MIR4435-2HG is widely expressed and might have a significant impact on the reshaping of the TNBC tumor microenvironment. Patients with TNBC in the high-MIR4435-2HG group may show reduced sensitivity to cisplatin, doxorubicin, and gemcitabine and have an increased propensity for immune escape. Knockdown of MIR4435-2HG inhibits cancer-associated fibroblasts (CAFs) activation. Notably, MIR4435-2HG predominantly enhances the migratory and invasive capabilities of TNBC cells through the epithelial-mesenchymal transition (EMT) process. Mechanistically, we validated that MIR4435-2HG activates the JNK/c-Jun and p38 non-classical MAPK signaling pathway in TNBC cells. ConclusionsOur findings highlight the significant potential of MIR4435-2HG as a highly promising biomarker for TNBC. Targeting MIR4435-2HG could represent an appealing therapeutic approach for TNBC.

Exploring the Role of Escherichia coli K-12 in Reducing MIR17HG Expression as a Poor Prognostic Biomarker in Colorectal Cancer

Background: Long noncoding RNAs (lncRNAs) play significant roles in various cellular processes, and alterations in their expression levels can contribute to the pathogenesis of colorectal cancer (CRC). Objectives: This study aims to identify lncRNAs highly associated with poor prognosis in CRC and determine those that exhibit significant expression changes under the influence of Escherichia coli K-12. Methods: Potentially susceptible lncRNAs to expression modulation in the presence of E. coli K-12 were identified by analyzing GSE50040 datasets. Data from the cancer genome Atlas (TCGA) were utilized to assess E. coli K-12-affected lncRNAs with the most significant impact on CRC pathogenesis. The association between the candidate lncRNA and patient prognosis was investigated using clinical data. The co-expression network was employed to identify pathways related to the identified lncRNA via the MsigDB database. To validate the in silico findings, CRC and adjacent normal samples were examined using the RT-qPCR method. Results: Cox regression analysis demonstrated that MIR17HG is a strong biomarker associated with poor prognosis in CRC patients. Increased expression of MIR17HG in cancer samples was correlated with key pathways involving cell proliferation, anti-apoptosis, and metastasis. RT-qPCR results showed that the expression level of MIR17HG in CRC samples was significantly higher than in normal samples. Further analysis revealed that MIR17HG expression is susceptible to suppression by E. coli K-12. Conclusions: High expression of MIR17HG in cancer samples is associated with an increased probability of mortality in CRC patients. Our study highlights the potential of E. coli K-12 to reduce CRC malignancy by downregulating MIR17HG expression.

Socioeconomic and Urban-Rural Disparities in Genome-Matched Treatment Receipt and Survival after Genomic Tumor Testing.

Emerging cancer treatments are often most available to socially advantaged individuals. This study examines the relationship of patient educational attainment, income level, and rurality to the receipt of genome-matched treatment (GMT) and overall survival. Survey and clinical data were collected from patients with cancer (n = 1258) enrolled in the Maine Cancer Genomics Initiative. Logistic regression models examined whether receipt of GMT differed by patient education, income, and rurality. Kaplan-Meier curves and Cox regression were conducted to evaluate 12-month mortality. We completed additional exploratory analyses using Kaplan-Meier curves and Cox models stratified by receipt of GMT. Both logistic and Cox regression models were adjusted for age and gender. Educational attainment, income level, and rurality were not associated with GMT receipt. Of 1258 patients, 462 (36.7%) died within 365 days of consent. Mortality risk was associated with lower educational attainment (hazard ratio (HR): 1.30; 95% CI: 1.06 to 1.59; p = .013). No statistically significant differences in mortality risk were observed for income level or rurality. Exploratory models suggest that patients who did not receive GMT with lower educational attainment had higher mortality risk (HR = 1.36, 95% CI: 1.09 to 1.69, p = .006). For patients who did receive GMT, there was no difference in mortality risk between the education groups (HR: 1.01, 95% CI: 0.56 to 1.81, p > .9). While there were no disparities in who received GMT, we found a disparity in mortality associated with education level, which was more pronounced for patients who did not receive GMT. Future research is warranted to investigate the intersectionality of social disadvantage with clinical outcomes to address survival disparities.

Abstract A080: Improving outcomes: Addressing racial and ethnic disparities in colorectal cancer genomic research

Abstract Colorectal cancer (CRC) is the fourth most common cancer diagnosed in the United States (U.S.). This disease presents notable health disparities among racial and ethnic minorities in the U.S. Native Americans (NA) and non-Hispanic Blacks (NHB) exhibit the highest incidence and mortality rates for CRC compared to non-Hispanic Whites (NHW). These disparities are driven by a combination of factors, including socioeconomic inequalities, access to healthcare, lifestyle habits, and genetic susceptibilities. Minority populations often face delays in diagnosis and treatment, leading to advanced disease stages at presentation and poorer outcomes. Addressing these disparities through cancer genomics is essential for developing effective, personalized treatments that can improve outcomes for underrepresented populations. Comprehensive genomic studies can reveal genetic mutations and biomarkers unique to these groups, facilitating targeted therapies and preventive measures tailored to their specific needs. To address these disparities, we conducted an analysis of U.S. population-based colorectal cancer studies within 3 cancer genomic databases: the National Cancer Institute’s Genomic Data Commons, the AACR Project GENIE, and cBioPortal. We identified 13 studies suitable for inclusion, calculating incidence percentages across all racial and ethnic categories. Our analysis encompassed a total of 20,295 patients. Among the analyzed patients, the racial distribution was as follows: NHW (68.5%), Asians (5.30%), NHB (7.7%), Other (5.6%), NA (0.2%), Pacific Islander/Native Hawaiian (0.07%), and not reported (12.7%). Ethnic data was missing for 24.1% (n=4,895) of the patients. Samples were predominantly from individuals identified as Not Hispanic (68.4%), while Hispanic individuals constituted 7.5%. Our results show significant underrepresentation of NHB, NA and Hispanic patients in CRC genomic databases highlighting a disparity between expected and actual representation. These findings underscore the critical need for inclusive research practices. Addressing these disparities in cancer genomics is imperative to develop equitable, effective treatments and improve health outcomes for all populations. Ensuring diverse representation in genomic databases will enhance the understanding of genetic differences across populations, inform targeted therapies, and ultimately contribute to reducing CRC disparities. By addressing these disparities, we can move towards a future where all populations benefit equally from advancements in CRC treatment and prevention, thus improving survival rates and quality of life for minority groups. Citation Format: Gabriela Arroyo Figueroa, Tim F. Greten, Cecilia Monge. Improving outcomes: Addressing racial and ethnic disparities in colorectal cancer genomic research [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A080.

Abstract B101: Knowledge, attitudes, and self-efficacy toward cancer genetic testing among Black women with and without breast cancer

Abstract Germline genetic testing for cancer risk offers opportunities for decision-making about screening and clinical risk management for individuals and their family members. Despite increasing availability of cancer genetic testing, Black individuals are still much less likely to receive or engage with testing compared to non-Hispanic white individuals. We sought to identify individual level factors influencing knowledge about and attitudes toward cancer genetic testing among Black women with and without breast cancer. Participants included 925 women from the Black Women’s Health Study who had previously provided a biospecimen for research and were invited to have their cancer genetic research findings confirmed via a CLIA-certified laboratory and learn their results as part of a randomized controlled trial. Prior to confirmation testing, all women completed a baseline questionnaire about personal and family history of cancer; prior genetic testing for hereditary cancer; and knowledge, attitudes, and confidence in one’s ability to use genetic information (genetics self-efficacy). We used linear regression to evaluate individual-level factors influencing cancer genetics knowledge, attitudes, and self-efficacy. Overall, mean knowledge score was 12.3 out of 16 (SD, 2.5); there were no differences in knowledge score between women who had a personal history of breast cancer and those who did not. While the majority of women answered most questions correctly, 20-30% of women were unable to correctly answer questions about validity of test results, clinical implications of a variant of uncertain significance, and legal protections against health insurance discrimination. Younger age, higher educational attainment, being married, and having had prior genetic testing were statistically significant predictors of higher total knowledge score. There were no differences in mean knowledge scores by first degree family history of breast cancer or personal history of breast or other cancer. Predictors of favorable attitudes and genetics self-efficacy included younger age, higher educational attainment, and being married. Women with a personal history of breast cancer had somewhat more favorable attitudes toward genetic testing compared to those with no prior history of breast cancer. In multivariable adjusted models, higher total knowledge was associated with more favorable attitudes and higher self-efficacy. In this cohort of highly educated Black women, overall cancer genetics knowledge was relatively high; however, evaluation of individual knowledge questions revealed opportunities for improvement in specific areas. Older women, those with lower educational attainment, and women who are not married or living as married may benefit from more targeted education about genetic cancer testing. Further, despite the role genetic testing currently plays in guiding cancer treatment, Black women who had breast cancer did not have higher knowledge scores than those without breast cancer and therefore may also benefit from targeted education. Citation Format: Kimberly A. Bertrand, Michelle Trevino-Talbot, Maggie Rudderman, Maureen Flynn, Howard J. Cabral, Julie R. Palmer, Catharine Wang. Knowledge, attitudes, and self-efficacy toward cancer genetic testing among Black women with and without breast cancer [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B101.

Abstract B055: Engaging Black and African American community members to develop culturally appropriate methods for cancer genetics education, risk assessment, and referral to research studies and clinical services: A community café approach

Abstract Background: Patients who have a potentially hereditary cancer (e.g., breast, ovarian, prostate) and self-identify as Black or African American (AA) are less likely to receive cancer genetic services than their White peers. Prior research indicates that the lack of consistent identification and referral of test-eligible patients and their family members is a significant barrier to receiving this care. Additionally, AA patients who do reach these services are much more likely than White patients to receive genetic test results that contain a variant of unknown significance (VUS). This disparity is largely attributable to the lower proportion of non-White patients included in cancer genetic research and clinically derived datasets. Developing culturally appropriate, community-informed, and community-based approaches to improve access to cancer genetic research and clinical care is critical to reducing these disparities. Methods: We used a community and patient engaged research (CPER) framework to develop and implement a series of community cafés. The foundation of the community café model is bi-directional engagement that emphasizes the critical roles of cultural awareness, empathy, and trust in healthcare and research improvement. Accordingly, we developed two brief educational modules that oriented café participants to the topics of 1) genetics and diversity in cancer research and 2) the role of family history in cancer risk assessment. Each ∼10 minute module was followed by a 30-40 minute facilitated listening session, enabling café participants to provide substantial feedback on both topics. Sessions were structured to generate input on the development of training and practice support materials for community health workers (CHWs) in the next phase of this research project. Note takers summarized the discussion at the end of each session, providing café participants an opportunity to revise or elaborate upon the written notes. Café sessions were also audio recorded for future transcription. Results: Eight community cafes were held from January-May 2024. Six cafes consisted of 121 AA community members (75.8% female; mean age = 53.4 years), most of whom had either been diagnosed with cancer (29.8%) or had a first-degree relative with cancer (31.4%). Two cafes enrolled a total of 21 CHWs (90.5% female; mean age = 45.4 years). Several actionable themes emerged during the listening sessions, including: clear explanations regarding why AA patients are being recruited into cancer genetic research studies, acknowledging harms of past race-based research; increased awareness of CHWs and how they can help build trust and bridge gaps between community members and academic medical centers. Café participants strongly endorsed increased presence of clinicians and researchers in community settings and increased representation of Black or African Americans on clinical and research teams. Impact: The community café approach was well received by community members, generating important input into the development of a community-based, equity-focused intervention. Citation Format: Erin Linnenbringer, Briana Wilson, Kayla Wallace, Anjali Kunavarapu, Charles Cogshell, Bailey Martin-Giacalone, Meera Muthukrishnan, Brett Maricque, Jessica Mozersky, Bettina Drake, Joyce Balls-Berry. Engaging Black and African American community members to develop culturally appropriate methods for cancer genetics education, risk assessment, and referral to research studies and clinical services: A community café approach [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B055.