Cancer Genome Research Articles

Equitable Access to Genomic Molecular Testing for Australian Cancer Patients: Insights from the Victorian Precision Oncology Summit.

The Victorian Precision Oncology Summit, convened in 2023, was a joint initiative between the Victorian Comprehensive Cancer Centre Alliance (VCCC Alliance) and the Monash Partners Comprehensive Cancer Consortium (MPCCC) and was proposed to guide a coordinated state-wide conversation about how the oncology sector can overcome some of the current obstacles in achieving equity of access to clinical cancer genomics for Victorian patients. Themes that emerged from discussion groups at the Summit include standardisation, centralisation, funding, education and communication and insights across those themes are outlined in this manuscript. The event served as a large consultation piece for the development of a broader precision oncology roadmap, which explores equitable access to molecular testing for Victorian patients, currently in development by the VCCC Alliance and MPCCC in collaboration with other key Victorian and national stakeholders. While this symposium was a Victorian initiative, it is felt that the insights garnered from this consultation piece will be of interest to consumer groups, clinicians, researchers, educators, policy makers and other key stakeholders in other states of Australia as well as in other countries implementing comprehensive genomic profiling within complex health systems.

Characterization of SUSD3 as a novel prognostic biomarker and therapeutic target for breast cancer.

Breast cancer (BC) remains a significant global health challenge, contributing substantially to cancer-related deaths worldwide. Its prevalence and associated death rates remain alarmingly high, highlighting the persistent public health burden. The objective of this study was to systematically examine the involvement of SUSD3 (Sushi Domain-Containing 3) in BC, highlighting its crucial role in the pathogenesis and progression of this disease. BC-related gene microarray data, along with corresponding clinicopathological information, were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Leveraging TIMER and HPA databases, we conducted comparative analyses to evaluate SUSD3 expression in BC. We then analyzed the association between SUSD3 and clinical traits, as well as the prognostic value of SUSD3. SUSD3-related differential expression genes (DEGs) were sent for analysis utilizing GO, KEGG, and GSEA. We utilized SUSD3 mRNA expression to assess immune cells' scores in BC tissues calculated by single-sample enrichment analyses based on "CIBERSORT" R package. Drug sensitivity analysis was used to screen potential drugs sensitive to SUSD3. R software was used for statistical analyses and graphical representation of the data. Our findings confirmed a significant upregulation of SUSD3 expression in BC, which correlated with a favorable prognosis. Clinical correlation analysis further emphasized the strong association between SUSD3 expression and key clinical parameters like estrogen receptor (ER) status, progesterone receptor (PR) status, stage, and T classification in breast cancer. Univariate and multivariate Cox regression analyses showed that SUSD3 could be used as an independent prognostic factor for BC. Differentially expressed genes (DEGs) co-expressed with SUSD3 were significantly associated with various biological processes, such as the cell cycle, DNA replication, p53 signaling pathway, cancer-related pathways, and Wnt signaling pathway, as indicated by gene set enrichment analysis (GSEA). Furthermore, our analysis demonstrated that SUSD3 generally exhibited negative associations with immune modulators. Drug sensitivity analysis revealed positive correlations between SUSD3 and the efficacy of Fulvestrant, Raloxifene, and Fluphenazine. The research emphasizes the significance of SUSD3 as a potential marker for BC, providing insights into the underlying molecular mechanisms implicated in tumorigenesis. SUSD3 holds promise in helping the classification of breast cancer pathological groups, predicting prognosis, and facilitating targeted therapy.

A python library for the fast and scalable computation of biologically meaningful individual specific networks

Individual Specific Networks (ISNs) are a tool used in computational biology to infer Individual Specific relationships between biological entities from omics data. ISNs provide insights into how the interactions among these entities affect their respective functions. To address the scarcity of solutions for efficiently computing ISNs on large biological datasets, we present ISN-tractor, a data-agnostic, highly optimized Python library to build and analyse ISNs. ISN-tractor demonstrates superior scalability and efficiency in generating Individual Specific Networks (ISNs) when compared to existing methods such as LionessR, both in terms of time and memory usage, allowing ISNs to be used on large datasets. We show how ISN-tractor can be applied to real-life datasets, including The Cancer Genome Atlas (TCGA) and HapMap, showcasing its versatility. ISN-tractor can be used to build ISNs from various -omics data types, including transcriptomics, proteomics, and genotype arrays, and can detect distinct patterns of gene interactions within and across cancer types. We also show how Filtration Curves provided valuable insights into ISN characteristics, revealing topological distinctions among individuals with different clinical outcomes. Additionally, ISN-tractor can effectively cluster populations based on genetic relationships, as demonstrated with Principal Component Analysis on HapMap data.

The clinical significance of endoplasmic reticulum stress related genes in non-small cell lung cancer and analysis of single nucleotide polymorphism for CAV1.

In recent years, protein homeostasis imbalance caused by endoplasmic reticulum stress has become a major hallmark of cancer. Studies have shown that endoplasmic reticulum stress is closely related to the occurrence, development, and drug resistance of non-small cell lung cancer, however, the role of various endoplasmic reticulum stress-related genes in non-small cell lung cancer is still unclear. In this study, we established an endoplasmic reticulum stress scores based on the Cancer Genome Atlas for non-small cell lung cancer to reflect patient features and predict prognosis. Survival analysis showed significant differences in overall survival among non-small cell lung cancer patients with different endoplasmic reticulum stress scores. In addition, endoplasmic reticulum stress scores was significantly correlated with the clinical features of non-small cell lung cancer patients, and can be served as an independent prognostic indicator. A nomogram based on endoplasmic reticulum stress scores indicated a certain clinical net benefit, while ssGSEA analysis demonstrated that there was a certain immunosuppressive microenvironment in high endoplasmic reticulum stress scores. Gene Set Enrichment Analysis showed that scores was associated with cancer pathways and metabolism. Finally, weighted gene co-expression network analysis displayed that CAV1 was closely related to the occurrence of non-small cell lung cancer. Therefore, in order to further analyze the role of this gene, Chinese non-smoking females were selected as the research subjects to investigate the relationship between CAV1 rs3779514 and susceptibility and prognosis of non-small cell lung cancer. The results showed that the mutation of rs3779514 significantly reduced the risk of non-small cell lung cancer in Chinese non-smoking females, but no prognostic effect was found. In summary, we proposed an endoplasmic reticulum stress scores, which was an independent prognostic factor and indicated immune characteristics in the microenvironment of non-small cell lung cancer. We also validated the relationship between single nucleotide polymorphism locus of core genes and susceptibility to non-small cell lung cancer.

Development and validation of a hypoxia- and mitochondrial dysfunction- related prognostic model based on integrated single-cell and bulk RNA sequencing analyses in gastric cancer.

Gastric cancer (GC) remains a major global health threat ranking as the fifth most prevalent cancer. Hypoxia, a characteristic feature of solid tumors, significantly contributes to the malignant progression of GC. Mitochondria are the major target of hypoxic injury that promotes mitochondrial dysfunction during the development of cancers including GC. However, the gene signature and prognostic model based on hypoxia- and mitochondrial dysfunction-related genes (HMDRGs) in the prediction of GC prognosis have not yet been established. The gene expression profile datasets of stomach cancer patients were retrieved from The Cancer Genome Atlas and the Gene Expression Omnibus databases. Prognostic genes were selected using Least Absolute Shrinkage andSelection Operator Cox (LASSO-Cox) regression analysis to construct a prognostic model. Immune infiltration was evaluated through ESTIMATE, CIBERSORT, and ssGSEA analyses. Tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were utilized to explore implications for immunotherapy. Furthermore, in vitro experiments were conducted to validate the functional roles of HMDRGs in GC cell malignancy. In this study, five HMDRGs (ZFP36, SERPINE1, DUSP1, CAV1, and AKAP12) were identified for developing a prognostic model in GC. This model stratifies GC patients into high- and low-risk groups based on median risk scores. A nomogram predicting overall survival (OS) was constructed and showed consistent results with observed OS. Immune infiltration analysis indicated that individuals in the high-risk group tend to exhibit increased immune cell infiltration. Additionally, analysis of cancer immunotherapy responses revealed that high-risk group patients exhibit poorer responses to cancer immunotherapy compared to the low-risk group. Immunohistochemistry (IHC) staining indicated that the expression levels of HMDRGs were remarkably correlated with GC, of which, SERPINE1 displayed the most pronounced up-regulation, while ZFP36 exhibited the most notable down-regulation in GC patients. Furthermore, in vitro investigation validated that SERPINE1 and ZFP36 contribute to the malignant processes of GC cells correlated with mitochondrial dysfunction. This study presents a novel and efficient approach to evaluate GC prognosis and immunotherapy efficacy, and also provides insights into understanding the pathogenesis of GC.

Unveiling an anoikis-related risk model and the role of RAD9A in colon cancer

ObjectiveColorectal cancer (CRC), specifically colon adenocarcinoma, is the third most prevalent and the second most lethal form of cancer. Anoikis is found to be specialized form of programmed cell death (PCD), which plays a pivotal role in tumor progression. This study aimed to investigate the role of the anoikis related genes (ARGs) in colon cancer. MethodsConsensus unsupervised clustering, differential expression analysis, tumor mutational burden analysis, and analysis of immune cell infiltration were utilized in the study. For the analysis of RNA sequences and clinical data of COAD patients, data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) were obtained. A prognostic scoring system for overall survival (OS) prediction was developed using Cox regression and LASSO regression analysis. Furthermore, loss-of-function assay was utilized to explore the role of RAD9A played in the progression of colon cancer. ResultsThe prognostic value of a risk score composed of NTRK2, EPHA2, RAD9A, CDC25C, and SNAI1 genes was significant. Furthermore, these findings suggested potential mechanisms that may influence prognosis, supporting the development of individualized treatment plans and management of patient outcomes. Further experiments confirmed that RAD9A could promote proliferation and metastasis of colon cancer cells. These effects may be achieved by affecting the phosphorylation of AKT. ConclusionDifferences in survival time and the tumor immune microenvironment (TIME) were observed between two gene clusters associated with ARGs. In addition, a prognostic risk model was established and confirmed as an independent risk factor. Furthermore, our data indicated that RAD9A promoted tumorigenicityby activating AKT in colon cancer.

22 Association of a germline single nucleotide polymorphism (SNP) in the interleukin-7 (IL7) gene with immune-related adverse events (irAEs)

Abstract Background Adverse events (AEs) can limit treatment immune checkpoint inhibitors (ICI) efficacy and worsen patient outcomes. Our group recently identified a germline IL7 SNP as a potential biomarker for prediction of irAEs (Groha, Nat Med 2022). In the current study, we sought to replicate the association between this IL7 SNP (rs16906115) and AEs in two clinical trials of patients with cancer treated with ICI regimens. Methods In the CheckMate-025 (CM025) trial (NCT01668784), involving patients with metastatic renal cell carcinoma (mRCC) randomized to either nivolumab (NIVO) or everolimus (EVE), whole-exome sequencing (WES) data from tumor and peripheral blood samples were analyzed. The Cancer Genome Analysis pipeline was utilized to identify somatic alterations, and the STITCH pipeline was employed to determine SNP carrier status. In the BinTA-0037 (BTA-0037) trial (NCT03631706), focusing on patients with metastatic non-small cell lung cancer (mNSCLC), the carrier status of a surrogate SNP rs16906062 (R2=0.66) was determined from tumor WES in the pembrolizumab (PEMBRO) arm. Within each treatment arm, time to incident AEs were compared between carriers (SNP+) and non-carriers (SNP-) via multivariable Cox regression, controlling for age, sex, race, ECOG and sample purity. A SNP´treatment interaction term was also included in the entire CM025 cohort. Censoring for AEs occurred at death or last follow-up. A recurrent event analysis for AEs was conducted using the Andersen-Gill model, controlling for the same variables. Additionally, overall survival (OS) and progression-free survival (PFS) were also assessed. Results In total, 534 pts were included (NIVO: n=189, PEMBRO: n=152, EVE: n=193), among which 82 (15.4%) were SNP+. There were no differences in clinical and pathological characteristics between SNP+ and SNP-, except for sex (SNP+ 16.1% vs. SNP- 30.1% in females, P=0.046). Similarly, no differences in somatic alterations, including single nucleotide and copy number variants were seen between SNP+ and SNP- in CM025. SNP carrier status had no effect on OS nor PFS in all treatment arms (all P≥0.22). The rate of grade 2+ AEs was significantly higher in SNP+ vs. SNP- in the NIVO arm (Figure A, HR=2.91[1.48-5.72]), but not in the EVE (Figure B, control, non-ICI) arm (HR=0.63[0.3-1.29], SNP´treatment Pinteraction=0.002). Similarly, the rate of all grade AEs in the PEMBRO arm of BTA-0037 was higher in SNP+ vs. SNP- (Figure C, HR=2.30[1.60-4.60]). The rate of recurrent grade 2+ AEs was also significantly higher in SNP+ vs. SNP- in the NIVO arm (HR=3.43[1.83-6.43]), whereas a trend for fewer recurrent grade 2+ AEs was seen in SNP+ vs. SNP- in the EVE arm (HR=0.46[0.17-1.25], SNP´treatment Pinteraction=0.0005). Figure: Kaplan-Meier curves showing the cumulative rate of adverse events in the NIVO (A) and EVE (B) arms of CM025, as well as the PEMBRO arm of BTA0037 (C), in SNP- and SNP+. Conclusions The IL7 SNP (rs16906115) is associated with significantly higher rates of grade 2+ AEs, including recurrent events, in pts with mRCC or mNSCLC treated with single agent PD-1 inhibitors but not with non-ICI regimens, with no effect on survival and efficacy outcomes. These results confirm the SNP’s predictive potential as a biomarker for irAEs to guide therapeutic decisions in pts treated with ICIs.

24 Applying genomic analysis to refine unclassified renal cell carcinoma

Abstract Background Despite the improvements in genomic and pathological techniques to identify renal cell carcinoma (RCC), 2-6% of all patients with RCC cannot be classified into a particular subgroup, thus called “unclassified” RCC (uRCC). Ascertaining the genomic profile of those patients may help select proper treatment and find novel targets. Methods The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) database v15.0 was used to select patients with RCC by using the OncoTree codes. All included patients were divided into four groups based on the most frequent subtypes of RCC: clear cell RCC (ccRCC), papillary RCC (pRCC), chromophobe RCC (chRCC), and uRCC. The Cancer Genome Atlas (TCGA) was additionally used to assess corresponding oncogenic signaling pathways. We employed the chi-squared test to compare categorical variables and applied the Benjamini-Hochberg correction to calculate Q-values, thereby controlling the false discovery rate. Results Overall, 1,990 tumor samples from 1,888 patients were evaluated. uRCC was observed in 184 patients (9.7%), whereas most had ccRCC (n=1339, 70.9%), followed by pRCC (n=224, 11.9%) and chRCC (n=141, 7.5%). Age distribution at sample sequencing was comparable between uRCC and other RCC subtypes (P>0.05). The proportion of female patients with uRCC was higher at 38.4%, compared to 26.5% in ccRCC (Q=0.002) and 16.3% in pRCC (Q<0.001), yet was comparable to chRCC at 48.6% (Q=0.210). The prevalence of uRCC was also greater among black patients, accounting for 8.6% vs. 2.1% in ccRCC (Q=0.001). Among patients with uRCC (n=224), the most common genomic alterations (GAs) were detected in NF2 (15.8%), SETD2 (15.8%), TP53 (13.9%), TERT (13.4%), and VHL (11.8%). NF2 alterations were also more prevalent in patients with uRCC than in patients with ccRCC (1.8%, Q<0.001), chRCC (0.7%, Q<0.001), and pRCC (5.8%, Q=0.058). Notably, median overall survival (OS) was poorer in uRCC patients with altered NF2 (n=29) than in those with unaltered NF2 (n=155, 30.7 vs. 87.1 months, p=0.058). Of patients with uRCC, 135 (72.5%) samples were from primary tumors and 39 (20.9%) from metastatic sites, with no difference in GA frequencies between the two. CDKN2A and CDKN2B were the most frequent co-mutated genes in uRCC (Q<0.001), followed by VHL and BAP1 (Q<0.001), and SETD2 and PBRM1 (Q=0.023). GAs in uRCC were primarily observed in pathways related to TP53 (42.8%), cell cycle (33.3%), PI3K (23.5%), and HIPPO (7.7%). Conclusions uRCC exhibited a unique genomic profile distinct from other common RCC subtypes. Notably, NF2 alterations were frequent and correlated with a poorer prognosis.

Nobiletin regulates the proliferation and migration of ovarian cancer A2780 cells via DPP4 and TXNIP.

Nobiletin is an active compound extracted from citrus fruits. Research has indicated that nobiletin has a potential inhibitory effect on ovarian cancer (OV). However, the mechanism of action remains unclear. The OV A2780 cells were treated using nobiletin, cell viability was examined using a cell counting kit-8 experiment, and cell migration was examined with a wound healing experiment. Nobiletin targets were retrieved from target databases. Differentially expressed genes (DEG) and weighted gene co-expression network analysis (WGCNA) were conducted on GSE26712 (OV). The intersection of the critical genes for nobiletin's action on OV and gene enrichment and immune infiltration analyses were performed. The Cancer Genome Atlas-OV data and molecular docking helped validate the findings. After adding nobiletin, cell viability and migration significantly decreased (P < 0.01). A total of 88 nobiletin targets and 1288 DEG were identified. The intersection genes were enriched inflammatory response and response to hypoxia. The most related module obtained from WGCNA contained 414 genes (correlation coefficient = 0.77, P < 0.01). DPP4 and TXNIP were recognized as the hub genes. The abundance of macrophages M2 and mast cells activated significantly enhanced with increased DPP4 expression (P < 0.05). The binding energy between DPP4/TXNIP and nobiletin was - 7.012/ - 7.184kcal/mol, forming 5/2 hydrogen bonds. Nobiletin effectively suppresses the viability and migration of OV A2780 cells. In this process, DPP4 and TXNIP are the key target, immune regulation, and oxidative stress playing significant roles.

Identifying and validating the roles of the cuproptosis-related gene DKC1 in cancer with a focus on esophageal carcinoma

BackgroundEsophageal cancer is a common malignancy of the digestive tract. Despite remarkable advancements in its treatment, the overall prognosis for patients remains poor. Cuproptosis is a form of programmed cell death that affects the malignant progression of tumors. This study aimed to examine the impact of the cuproptosis-associated gene DKC1 on the malignant progression of esophageal cancer.MethodsClinical and RNA sequencing data of patients with esophageal cancer were extracted from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis was used to identify the differentially expressed genes related to cuproptosis that are associated with prognosis. We then validated the difference in the expression of DKC1 between tumor and normal tissues via three-dimensional multiomics difference analysis. Subsequently, we investigated the association between DKC1 expression and the tumor microenvironment by employing the TIMER2.0 algorithm, which was further validated in 96 single-cell datasets obtained from the TISCH database. Additionally, the functional role of DKC1 in pancarcinoma was assessed through GSEA. Furthermore, a comprehensive pancancer survival map was constructed, and the expression of DKC1 was verified in various molecular subtypes. By utilizing the CellMiner, GDSC, and CTRP databases, we successfully established a connection between DKC1 and drug sensitivity. Finally, the involvement of DKC1 in the progression of esophageal cancer was investigated through in vivo and in vitro experiments.ResultsIn this study, we identified a copper death-related gene, DKC1, in esophageal cancer. Furthermore, we observed varying levels of DKC1 expression across different tumor types. Additionally, we conducted an analysis to determine the correlation between DKC1 expression and clinical features, revealing its association with common cell cycle pathways and multiple metabolic pathways. Notably, high DKC1 expression was found to indicate poor prognosis in patients with various tumors and to influence drug sensitivity. Moreover, our investigation revealed significant associations between DKC1 expression and the expression of molecules involved in immune regulation and infiltration of lymphocyte subtypes. Ultimately, the increased expression of DKC1 in esophageal cancer tissues was verified using clinical tissue samples. Furthermore, DKC1-mediated promotion of esophageal cancer cell proliferation and migration was confirmed through both in vitro and in vivo experiments. Additionally, it is plausible that DKC1 may play a role in the regulation of cuproptosis.ConclusionIn this study, we conducted a systematic analysis of DKC1 and its regulatory factors and experimentally validated its excellent diagnostic and prognostic abilities in various cancers. Further research indicated that DKC1 may reshape the tumor microenvironment (TME), highlighting the potential of DKC1-based cancer treatment and its usefulness in predicting the response to chemotherapy.

Integrated single-cell and bulk RNA sequencing analyses identify an immunotherapy nonresponse-related fibroblast signature in gastric cancer.

Factors that determine nonresponse to immune checkpoint inhibitor (ICI) remain unclear. The protumor activities of cancer-associated fibroblasts (CAFs) suggest that they are potential therapeutic targets for cancer treatment. There is, however, a lack of CAF-related signature in predicting response to immunotherapy in gastric cancer (GC). Single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data of GC immunotherapy were downloaded from the Gene Expression Omnibus database. Bulk RNA-seq data were obtained from The Cancer Genome Atlas. The R package 'Seurat' was used for scRNA-seq data processing. Cellular infiltration, receptor-ligand interactions, and evolutionary trajectory analysis were further explored. Differentially expressed genes affecting overall survival were obtained using the limma package. Weighted Gene Correlation Network Analysis was used to identify key modules of immunotherapy nonresponder. Prognostic model was constructed by univariate Cox and least absolute contraction and selection operator analysis using the intersection of activated fibroblast genes (AFGs) with key module genes. The differences in clinicopathological features, immune microenvironment, immunotherapy prediction, and sensitivity to small molecule agents between the high- and low-risk groups were further investigated. Based on scRNA-seq, we finally identified 20 AFGs associations with the prognosis of GC patients. AFGs' high expression levels were correlated with both poor prognosis and tumor progression. Three genes (FRZB, SPARC, and FKBP10) were identified as immunotherapy nonresponse-related fibroblast genes and used to construct the prognostic signature. This signature is an independent significant risk factor affecting the clinical outcomes of GC patients. Remarkably, there were more CD4 memory T cells, resting mast cells, and M2 macrophages infiltrating in the high-risk group, which was characterized by higher tumor immune exclusion. Moreover, patients with higher risk scores were more prone to not respond to immunotherapy but were more sensitive to various small molecule agents, such as memantine. In conclusion, this study constructed a fibroblast-associated ICI nonresponse gene signature, which could predict the response to immunotherapy. This study potentially revealed a novel way to overcome immune resistance in GC.

A glycolysis-related signature to improve the current treatment and prognostic evaluation for breast cancer.

As a heterogeneous malignancy, breast cancer (BRCA) shows high incidence and mortality. Discovering novel molecular markers and developing reliable prognostic models may improve the survival of BCRA. The RNA-seq data of BRCA patients were collected from the training set The Cancer Genome Atlas (TCGA)-BRCA and validation set GSE20685 in the Gene Expression Omnibus (GEO) databases. The "GSVA" R package was used to calculate the glycolysis score for each patient, based on which all the patients were divided into different glycolysis groups. The "limma" package was employed to perform differentially expression genes (DEGs) analysis. Key signature genes were selected by performing un/multivariate and least absolute shrinkage and selection operator (LASSO) C regression and used to develop a RiskScore model. The ESTIMATE and MCP-Counter algorithms were used for quantifying immune infiltration level. The functions of the genes were validated using Western blot, colony formation, transwell and wound-healing assay. The glycolysis score and prognostic analysis showed that high glycolysis score was related to tumorigenesis pathway and a poor prognosis in BRCA as overactive glycolysis inhibited the normal functions of immune cells. Subsequently, we screened five key prognostic genes using the LASSO Cox regression analysis and used them to establish a RiskScore with a high classification efficiency. Based on the results of the RiskScore, it was found that patients in the high-risk group had significantly unfavorable immune infiltration and prognostic outcomes. A nomogram integrating the RiskScore could well predict the prognosis for BRCA patients. Knockdown of PSCA suppressed cell proliferation, invasion and migration of BRCA cells. This study developed a glycolysis-related signature with five genes to distinguish between high-risk and low-risk BRCA patients. A nomogram developed on the basis of the RiskScore was reliable to predict BRCA survival. Our model provided clinical guidance for the treatment of BRCA patients.

14 Natural killer cells have impaired cytotoxicity in advanced renal cell carcinoma

Abstract Background Natural killer (NK) cells are key mediators of anti-tumor activity in multiple cancers, including clear cell renal cell carcinoma (ccRCC). However, the phenotype and function of NK cells across different disease stages of ccRCC is incompletely characterized. Methods Single-cell RNA (scRNA)-sequencing (10x Genomics) data from tumor and adjacent normal kidney from ccRCC was analyzed at multiple clinical stages (localized – stage I/II/III; and advanced – stage IV). Graph-based clustering and lineage markers were used to identify distinct NK cell populations. Differential gene expression analysis was performed to further investigate NK cell phenotype and to derive a gene expression signature (GES). Gene signatures from NK cell subclusters of interest were used to interrogate bulk transcriptomic datasets and expression with clinical outcomes. Tumor-infiltrating NK cell function (cytokine production and cytotoxicity) was assessed by isolation of live NK cells from ccRCC tissue, co-culture with K562 target cells, and measurement of cytokine (IFNgamma) and cytotoxicity (CD107a) markers by flow cytometry. Results Single-cell transcriptomic data were analyzed from 13 patients with ccRCC (tumor and normal kidney), resulting in 21,139 high-quality NK cells. Patients with advanced/metastatic RCC had a lower proportion of NK cells versus total immune cells in the tumor microenvironment compared to normal kidney (p=0.036) and localized ccRCC (p=0.088). Clustering analysis revealed 6 distinct NK cell subsets. The C0.Bright-like NK cell cluster was significantly enriched in advanced ccRCC compared to localized ccRCC (p=0.048) and normal kidney (p=0.0059), expressed markers of tissue residency (ZNF683, ITGA1, CD9, ITGAE), and had decreased expression of cytotoxicity genes (GZMB, PRF1). A GES signature composed of genes upregulated in the dysfunctional C0.Bright-like NK cell cluster was used to interrogate bulk RNA-sequencing data from The Cancer Genome Atlas clear cell cohort, providing validation in a large, independent cohort, of an increase in this dysfunctional NK subset in advanced ccRCC compared to localized ccRCC (p=0.00039) and normal tissue (p=5.3e-05). To functionally confirm the decreased cytotoxicity of this dysfunctional NK population, CD45+CD56+CD3- NK cells were isolated from advanced ccRCC, and co-cultured with K562 target cells. Consistent with the transcriptomic phenotype, tumor-resident CD49a+CD9+ NK cells had cytokine production (IFNgamma) but decreased markers of cytotoxicity (CD107a) compared to CD49a-CD9- NK cells. By contrast, CD49a+CD9+ NK cells isolated from peripheral blood or normal kidney tissue maintained cytotoxic activity. Conclusions Among patients with ccRCC, a single-cell transcriptomic analysis revealed heterogeneous NK cell populations. A dysfunctional tumor resident NK cell phenotype was enriched among patients with advanced disease in ccRCC, and functionally confirmed to have diminished cytotoxicity. This study therefore provides insight into a new axis of immune dysfunction – decreased NK-mediated cytotoxicity – in advanced ccRCC. An improved understanding of NK cell dysfunction within ccRCC may provide a foundation for therapeutic restoration of NK-mediated anti-tumor activity in ccRCC. DOD CDMRP Funding: yes

74 Unraveling the Complexities of Obesity in Clear Cell Renal Cell Carcinoma Carcinogenesis

Abstract Background Obesity has been identified as an established risk factor in the development of clear cell renal cell carcinoma (ccRCC). ccRCC arises from the proximal convoluted tubule (PCT) of the kidney which is also the site of obesity-associated chronic kidney disease. Obesity can lead to chronic cellular insults which may lead to DNA injury and whether these mechanisms are critical to cancer initiation in the kidney is unclear. One potential way that obesity can lead to cancer is by altering lipid metabolism, including increasing circulating saturated fatty acids. In particular, palmitic acid is known to be lipotoxic to proximal tubules of the kidney. Understanding how free fatty acids initiate cancer is critical to understanding the role of obesity in cancer initiation and development. We hypothesize that chronic injury and repair due to excess FFA exposure could lead to ccRCC carcinogenesis and aim to define the metabolic phenotype of obesity associated ccRCC. Methods Using publicly available data from The KIRC Cancer Genome Atlas Program (TCGA) and clinicopathologic data, we compared the RNAseq profiles of obese (BMI &amp;gt;= 30) to normal weight (BMI =&amp;lt; 25) sample origins. Of the 337, a total of 333 had BMI available for analysis. We evaluated differences in Hallmark and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Using DESeq, we adjusted for age and sex. In vitro, HK PCT cells were cultured in DMEM+10%FBS treated with bovine serum albumin (BSA)-palmitic acid complex for 48 hrs. We measured cell viability using Alamar Blue. Results were normalized to controls with BSA only. We extracted protein and performed western blots to identify DNA damage (pATM, H2AX) and endoplasmic reticulum stress (ATF4, eFI2alpha). Results Most of the patients in our clinical data cohort are male (64.4%), while 45.4% of patients are categorized by BMI as obese and 33.2% are categorized as normal. We utilized 333 individuals from the Kyoto Encyclopedia of Genes and Genomes (KEGG) to link genomic information to pathways associated with fatty acid metabolism as well as other cancer-associated hallmark metabolic pathways. We confirmed that excess free fatty acid supplementation leads to decreased cell viability in renal proximal tubule cells and renal embryonal cells and aim to assess differences in gene expression and metabolomic variation with fatty acid supplementation. Conclusions Through the investigation of these questions, we hope to improve understanding of obesity associated ccRCC and ultimately impact oncological outcomes for patients with this cancer. Understanding changes in lipid metabolism around ccRCC initiation will help identify novel pathways for pharmacologic intervention at earlier stages of the disease. DOD CDMRP Funding: yes

PRNP is a pan-cancer prognostic and immunity-related to EMT in colorectal cancer.

Prion protein gene (PRNP) is widely expressed in a variety of tissues. Although the roles of PRNP in several cancers have been investigated, no pan-cancer analysis has revealed its relationship with tumorigenesis and immunity. Comprehensive analyses were conducted on The Cancer Genome Atlas (TCGA) Pan-Cancer dataset from the University of California Santa Cruz (UCSC) database to determine the expression of PRNP and its potential prognostic implications. Immune infiltration and enrichment analysis methods were used to ascertain correlations between PRNP expression levels, tumor immunity, and immunotherapy. Additionally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were employed to examine possible signaling pathways involving PRNP. In vitro experiments using CCK-8 assay, Wound healing assay, and Transwell assay to detect the effect of Cellular prion protein (PrPC) on proliferation, migration, and invasion in colorectal cancer (CRC) cells. The expression levels of epithelial-mesenchymal transition (EMT)-related proteins (N-cadherin, E-cadherin, Vimentin and Snail) were detected by western blot. Among most cancer types, PRNP is expressed at high levels, which is linked to the prognosis of patients. PRNP expression is strongly associated with immune infiltrating cells, immunosuppressive cell infiltration and immune checkpoint molecules. In addition to tumor mutation burden (TMB), substantial correlations are detected between PRNP expression and microsatellite instability (MSI) in several cancers. In vitro cell studies inferred that PrPC enhanced the proliferation, migration, invasion, and EMT of CRC cells. PRNP serves as an immune-related prognostic marker that holds promise for predicting outcomes related to CRC immunotherapy while simultaneously promoting cell proliferation, migration, and invasion activities. Furthermore, it potentially plays a role in governing EMT regulation within CRC.

A model-free and distribution-free multi-omics integration approach for detecting novel lung adenocarcinoma genes

Detection of important genes affecting lung adenocarcinoma (LUAD) is critical to finding effective therapeutic targets for this highly lethal cancer. However, many existing approaches have focused on single outcomes or phenotypic associations, which may not be as thorough as investigating molecular transcript levels within cells. In this article, we apply a novel multivariate rank-distance correlation-based gene selection procedure (MrDcGene) to LUAD multi-omics data downloaded from The Cancer Genome Atlas (TCGA). MrDcGene provides additional opportunities for detecting novel susceptibility genes as it leverages information from multiple platforms, while efficiently handling challenges such as high dimensionality, low signal-to-noise ratio, unknown distributions, and non-linear structures, etc. Notably, the MrDcGene method is able to detect two different scenarios, i.e., strong association strength with a few gene expressions and weak association strength with several gene expressions. After thoroughly exploring the association between gene expression (GE) and multiple other platforms, including reverse phase protein array (RPPA), miRNA, copy number variation (CNV) and DNA methylation (ME), we detect several novel genes that may play an important role in LUAD (ZNF133, CCDC159, YWHAZ, HNRNPR. ITPR2, PTHLH, and WIPI2). In addition, we quantitatively validate several other susceptibility genes that were reported in the literature using different methods and studies. The accuracy of the MrDcGene approach is theoretically assured and empirically demonstrated by the simulation studies.

RBM25 depletion suppresses the growth of colon cancer cells through regulating alternative splicing of MNK2.

Increasing evidence suggests that deregulated RNA splicing factors play critical roles in tumorigenesis; however, their specific involvement in colon cancer remains largely unknown. Here we report that the splicing factor RBM25 is overexpressed in colon cancer, and this increased expression correlates with a poor prognosis of patients with colon cancer. Functionally, RBM25 ablation suppresses the growth of colon cancer cells both in vitro and in vivo. Mechanistically, our transcriptome-wide analysis of splicing events revealed that RBM25 regulates a large number of cancer-related alternative splicing events across the human genome in colon cancer. Particularly, RBM25 regulates the splicing of MNK2 by interacting with the poly G rich region in exon 14a, thereby inhibiting the selection of the proximal 3' splice site (ss), resulting in the production of the oncogenic short isoform, MNK2b. Knockdown of RBM25 leads to an increase in the MNK2a isoform and a decrease in the MNK2b isoform. Importantly, re-expression of MNK2b or blocking the 3' ss of the alternative exon 14a with ASO partially reverses the RBM25 knockdown mediated tumor suppression. Moreover, MNK2b levels were significantly increased in colon cancer tissues, which is positively correlated with the expression level of RBM25. Collectively, our findings uncover the critical role of RBM25 as a key splicing factor in colon cancer, suggesting its potential as a prognostic marker and therapeutic target.

Tropomodulin 3 Overexpression as a Marker for Platinum Resistance and Immune Infiltration in Ovarian Cancer.

The cytoskeleton plays an important role in platinum resistance in ovarian cancer. Tropomodulin 3 (TMOD3) is critical in the development of many tumors, but its role in the drug resistance of ovarian cancer remains unexplored. By analyzing data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and Clinical Proteomic Tumor Analysis Consortium (CPTAC) databases, this study compared TMOD3 expression in ovarian cancer and normal tissues, and examined the expression of TMOD3 after platinum treatment in platinum-sensitive and platinum-resistant ovarian cancers. The Kaplan-Meier method was used to assess the effect of TMOD3 on overall survival (OS) and progression-free survival (PFS) in ovarian cancer patients. microRNAs (miRNAs) targeting TMOD3 were predicted using TargetScan and analyzed using the TCGA database. Tumor Immune Estimation Resource (TIMER) and an integrated repository portal for tumor-immune system interactions (TISIDB) were used to determine the relationship between TMOD3 expression and immune infiltration. TMOD3 coexpression networks in ovarian cancer were explored using LinkedOmics, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), and The Database for Annotation, Visualization, and Integrated Discovery (DAVID) Bioinformatics. The results showed that TMOD3 was highly expressed in ovarian cancer and was associated with the grading, staging, and metastasis of ovarian cancer. TMOD3 expression was significantly reduced in platinum-treated ovarian cancer cells and patients. However, TMOD3 expression was higher in platinum-resistant ovarian cancer cells and tissues compared to platinum-sensitive ones. Higher TMOD3 expression was significantly associated with lower OS and PFS in ovarian cancer patients treated with platinum-based chemotherapy. miRNA-mediated post-transcriptional regulation is likely responsible for high TMOD3 expression in ovarian cancer and platinum-resistant ovarian tissues. The expression of TMOD3 mRNA was associated with immune infiltration in ovarian cancer. These findings indicate that TMOD3 is highly expressed in ovarian cancer and is closely associated with platinum resistance and immune infiltration.

Copy number alterations in metastatic and early breast tumours: prognostic and acquired biomarkers of resistance to CDK4/6 inhibitors

BackgroundCopy number alterations (CNA) are acquired during the evolution of cancers from their early stage to metastatic stage. This study aims at analysing the clinical value of the identified metastasis-associated CNAs both in metastatic breast cancers (mBCs) and early breast cancers (eBCs).MethodsSingle-nucleotide polymorphism (SNP)-array was performed on 926 biopsies from mBC patients, enrolled in SAFIR02-BREAST prospective trial. CNA profiles of eBCs from The Cancer Genome Atlas Breast Invasive Carcinoma (n = 770), Molecular Taxonomy of Breast Cancer International Consortium (n = 1620) and PACS04 trial (n = 243) cohorts were used as references for comparing mBCs and eBCs CNA profiles. Overall survival was the considered survival endpoint.ResultsAmong the twenty-one genes frequently altered in ER + /HER2− mBCs: focal amplification of TERT was associated with poor outcome in the ER + /HER2− mBC population. Among the ER + /HER2− mBCs patients for whom CDK4/6 inhibitors information before biopsies collection was available: we identified seven genes on post-treatment biopsies, including the cyclin-dependent kinase 4 (CDK4), which was amplified in 9.8% of the ER + /HER2− mBCs pretreated population, as compared to 1.5% in the ER + /HER2− mBCs unpretreated population (P = 2.82E-04) as well as the 3 eBC populations. CDK4 amplification was associated with poor outcome in the ER + /HER2− eBCs.ConclusionsThis study provides insights into the biology of mBCs and identifies clinically useful genomic features for future improvement of breast cancer patient management.

WD repeat domain 43 as a new predictive indicator and its connection with tumor immune cell infiltration in pan-cancer.

WD repeat domain 43 (WDR43) is a protein component that encodes WD-repeats and is involved in ribosome biogenesis. However, little is known about the role of WDR43 in cancer prognosis and immune modulation. In this study, we analyzed the expression and prognostic significance of WDR43 in pan-cancer using the Cancer Genome Atlas, the Genotype-Tissue Expression, and the Human Protein Atlas. We also examined the differential expression of WDR43 in liver hepatocellular carcinoma (LIHC) and adjacent tissues of 48 patients using immunohistochemistry. Additionally, we investigated the correlation between WDR43 and clinical characteristics, gene alterations, tumor mutation burden, microsatellite instability, mismatch repair, tumor microenvironment, immune infiltrating cells, and immune-related genes using bioinformatics methods. Gene set enrichment analysis was conducted, and potential biological mechanisms were identified. Immunohistochemistry staining showed that WDR43 was overexpressed in LIHC among 48 patients. Upregulation of WDR43 was associated with unfavorable prognosis, including overall survival in various types of cancer such as LIHC, uterine corpus endometrial cancer, head and neck squamous cell carcinoma, and pancreatic adenocarcinoma. Differential expression of WDR43 was significantly correlated with microsatellite instability, mismatch repair, and immune cell infiltration. Gene ontology annotation analysis revealed that these genes were significantly enriched in immune-related functions, including immune response, immune regulation, and signaling pathways. We conducted a thorough investigation of the clinical features, phases of tumor development, immune infiltration, gene mutation, and functional enrichment analysis of WDR43 in various types of cancer. This research offers valuable insight into the significance and function of WDR43 in clinical therapy.