Tumor Transcriptomes Research Articles

Abstract C102: Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York

Abstract Prompted by the considerable biases toward European ancestry cases in large cancer genomics repositories, the New York Genome Center initiated an effort to diversify the public datasets that are forming the foundations of current cancer research, in order to optimize the unbiased applications of modern genomically-driven discoveries to a larger population. Our effort was focused on 8 cancer types (breast, prostate, bladder, lung, pancreatic, colon and endometrial cancer, as well as multiple myeloma) and generated Illumina tumor-normal whole-genome sequencing and tumor transcriptome sequencing. The majority of the samples were retrospectively obtained in clinics and hospitals of the New York region and the analyses are conducted with collaborators in these institutions. Our dataset is currently composed of 851 tumor-normal WGS and 471 RNASeq, and is progressively being distributed to the scientific community in partnership with ICGC-ARGO. Overall, 75% of the cohort is predominantly of non-European ancestry, as estimated by genetic ancestry analysis using the 1000Genomes continental references.We analyzed the samples with NYGC’s somatic variant calling pipeline and will present results from the 8 cancer types related to germline and somatic variants (single-nucleotide variants, indels, copy-number alterations, complex structural variants) as well as mutational signatures, neoantigen prediction, fusion genes and expression profiles, in relation to genetic ancestry estimation and clinical features of the patients. We anticipate that the dataset will significantly diversify the genetic ancestry of tumor profiles in public databases, and serve to form hypotheses regarding the contribution of ancestry on cancer disparities. The experience of the Polyethnic-1000 project informs our contribution to the Cancer Grand Challenge SAMBAI, which focuses on breast, prostate and pancreatic cancers in the African Diaspora. SAMBAI will further investigate the causes of cancer disparity by combining genomic data with social determinants of health and exposomics information, deeper immune profiling and new genomics technologies such as long reads sequencing and the use of a pangenome reference. Citation Format: Nicolas Robine, Lara Winterkorn, Tim Chu, Zoe Goldstein, Will Hooper, Ali Oku, Heather M. Geiger, Melissa B. Davis, Onyinye Balogun. Polyethnic-1000: Advancing cancer genomics by studying ethnically diverse, underserved patient populations in New York [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 C102.

Innate immunity gene Nod2 protects mice from orthotopic breast cancer

BackgroundNod2 is involved in innate immune responses to bacteria, regulation of metabolism, and sensitivity to cancer. A Nod2 polymorphism is associated with breast cancer, but the role of Nod2 in the development and progression of breast cancer is unknown.MethodsHere, we tested the hypothesis that Nod2 protects mice from breast cancer using the 4T1 orthotopic model of mammary tumorigenesis. WT and Nod2−/− mice were injected with 4T1 mammary carcinoma cells and the development of tumors was monitored. A detailed analysis of the tumor transcriptome was performed and genes that were differentially expressed and pathways that were predicted to be altered between WT and Nod2−/− mice were identified. The activation of key signaling molecules involved in metabolism and development of cancer was studied.ResultsOur data demonstrate that Nod2−/− mice had a higher incidence and larger tumors than WT mice. Nod2−/− mice had increased expression of genes that promote DNA replication and cell division, and decreased expression of genes required for lipolysis, lipogenesis, and steroid biosynthesis compared with WT mice. Nod2−/− mice also had lower expression of genes required for adipogenesis and reduced levels of lipids compared with WT mice. The tumors in Nod2−/− mice had decreased expression of genes associated with PPARα/γ signaling, increased activation of STAT3, decreased activation of STAT5, and no change in the activation of ERK compared with WT mice.ConclusionsWe conclude that Nod2 protects mice from the 4T1 orthotopic breast tumor, and that tumors in Nod2−/− mice are predicted to have increased DNA replication and cell proliferation and decreased lipid metabolism compared with WT mice.

Dissecting transcriptome signals of anti-PD-1 response in lung adenocarcinoma

Immune checkpoint blockades are actively adopted in diverse cancer types including metastatic melanoma and lung cancer. Despite of durable response in 20–30% of patients, we still lack molecular markers that could predict the patient responses reliably before treatment. Here we present a composite model for predicting anti-PD-1 response based on tumor mutation burden (TMB) and transcriptome sequencing data of 85 lung adenocarcinoma (LUAD) patients who received anti-PD-(L)1 treatment. We found that TMB was a good predictor (AUC = 0.81) for PD-L1 negative patients (n = 20). For PD-L1 positive patients (n = 65), we built an ensemble model of 100 XGBoost learning machines where gene expression, gene set activities and cell type composition were used as input features. The transcriptome-based models showed excellent accuracy (AUC > 0.9) and highlighted the contribution of T cell activities. Importantly, nonresponder patients with high prediction score turned out to have high CTLA4 expression, which suggested that neoadjuvant CTLA4 combination therapy might be effective for these patients. Our data and analysis results provide valuable insights into developing biomarkers and strategies for treating LUAD patients using immune checkpoint inhibitors.

Systematic transcriptomic analysis of childhood medulloblastoma identifies N6- methyladenosine-dependent lncRNA signatures associated with molecular subtype, immune cell infiltration, and prognosis.

Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4+ naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes METTL3 and METTL14 in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our in silico analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.

Systematic transcriptomic analysis of childhood medulloblastoma identifies N6-methyladenosine-dependent lncRNA signatures associated with molecular subtype, immune cell infiltration, and prognosis

Medulloblastoma, the most common malignant pediatric brain tumor, is classified into four main molecular subgroups, but group 3 and group 4 tumors are difficult to subclassify and have a poor prognosis. Rapid point-of-care diagnostic and prognostic assays are needed to improve medulloblastoma risk stratification and management. N6-methyladenosine (m6A) is a common RNA modification and long non-coding RNAs (lncRNAs) play a central role in tumor progression, but their impact on gene expression and associated clinical outcomes in medulloblastoma are unknown. Here we analyzed 469 medulloblastoma tumor transcriptomes to identify lncRNAs co-expressed with m6A regulators. Using LASSO-Cox analysis, we identified a five-gene m6A-associated lncRNA signature (M6LSig) significantly associated with overall survival, which was combined in a prognostic clinical nomogram. Using expression of the 67 m6A-associated lncRNAs, a subgroup classification model was generated using the XGBoost machine learning algorithm, which had a classification accuracy > 90%, including for group 3 and 4 samples. All M6LSig genes were significantly correlated with at least one immune cell type abundance in the tumor microenvironment, and the risk score was positively correlated with CD4+ naïve T cell abundance and negatively correlated with follicular helper T cells and eosinophils. Knockdown of key m6A writer genes METTL3 and METTL14 in a group 3 medulloblastoma cell line (D425-Med) decreased cell proliferation and upregulated many M6LSig genes identified in our in silico analysis, suggesting that the signature genes are functional in medulloblastoma. This study highlights a crucial role for m6A-dependent lncRNAs in medulloblastoma prognosis and immune responses and provides the foundation for practical clinical tools that can be rapidly deployed in clinical settings.

In silico RNA isoform screening to identify potential cancer driver exons with therapeutic applications

Alternative splicing is crucial for cancer progression and can be targeted pharmacologically, yet identifying driver exons genome-wide remains challenging. We propose identifying such exons by associating statistically gene-level cancer dependencies from knockdown viability screens with splicing profiles and gene expression. Our models predict the effects of splicing perturbations on cell proliferation from transcriptomic data, enabling in silico RNA screening and prioritizing targets for splicing-based therapies. We identified 1,073 exons impacting cell proliferation, many from genes not previously linked to cancer. Experimental validation confirms their influence on proliferation, especially in highly proliferative cancer cell lines. Integrating pharmacological screens with splicing dependencies highlights the potential driver exons affecting drug sensitivity. Our models also allow predicting treatment outcomes from tumor transcriptomes, suggesting applications in precision oncology. This study presents an approach to identifying cancer driver exon and their therapeutic potential, emphasizing alternative splicing as a cancer target.

Transcriptome- and proteome-wide association studies identify genes associated with renal cell carcinoma

We performed a series of integrative analyses including transcriptome-wide association studies (TWASs) and proteome-wide association studies (PWASs) of renal cell carcinoma (RCC) to nominate and prioritize molecular targets for laboratory investigation. On the basis of a genome-wide association study (GWAS) of 29,020 affected individuals and 835,670 control individuals and prediction models trained in transcriptomic reference models, our TWAS across four kidney transcriptomes (GTEx kidney cortex, kidney tubules, TCGA-KIRC [The Cancer Genome Atlas kidney renal clear-cell carcinoma], and TCGA-KIRP [TCGA kidney renal papillary cell carcinoma]) identified 38 gene associations (false-discovery rate <5%) in at least two of four transcriptomic panels and identified 12 genes that were independent of GWAS susceptibility regions. Analyses combining TWAS associations across 48 tissues from GTEx identified associations that were replicable in tumor transcriptomes for 23 additional genes. Analyses by the two major histologic types (clear-cell RCC and papillary RCC) revealed subtype-specific associations, although at least three gene associations were common to both subtypes. PWAS identified 13 associated proteins, all mapping to GWAS-significant loci. TWAS-identified genes were enriched for active enhancer or promoter regions in RCC tumors and hypoxia-inducible factor binding sites in relevant cell lines. Using gene expression correlation, common cancers (breast and prostate) and RCC risk factors (e.g., hypertension and BMI) display genetic contributions shared with RCC. Our work identifies potential molecular targets for RCC susceptibility for downstream functional investigation.

Analysis of heterochromatin remodeling as a mechanism of radiotherapy (RT) resistance through molecular profiling of radioresistant (RR) head and neck (HNC) and prostate cancers (PCa).

137 Background: Resistance to RT remains a clinical challenge, given our limited understanding of the molecular pathways underpinning radioresistance. Here, we investigated for mechanisms linked to RR using paired experimental and clinico-molecular HNC and PCa datasets for discovery and validation of novel pathways that may be enriched in RR cancers. Methods: For experimental data, we generated RR HNC (FaDu, HK1) and PCa (22Rv1, DU145) cell lines following high-dose X-irradiation (90 Gy in 45 fr). Genotypic characterization of RR and wildtype (WT) cells was performed by genomic and transcriptomic sequencing using WES (100X) and RNAseq (Illumina, CA), respectively, followed by functional characterization by western blot (WB) and immunofluorescence (IF). For clinico-molecular data, we utilized two prospectively recruited RT cohorts, consisting of 311 patients with HNC (n=158) and PCa (n=153). Tumor transcriptomes were profiled using RNAseq and Affymetrix ST array (ThermoFisher, CA), respectively. Comparative analyses of molecular profiles were first performed between RR and WT in vitro models to identify dysregulated pathways that were linked to radioresistance, and subsequently tested for association with disease-free survival (DFS) in the clinical cohorts. Results: Comparative genomic analyses between RR and WT HNC and PCa models revealed an abundance of acquired mutations in the RR compared with WT models, with a higher mutation count observed in PCa than HNC cells (SNV counts: 2,158 [DU145-RR] and 1,387 [22Rv1-RR] vs 396 [FaDu-RR] and 25 [HK1-RR], P&lt;0.0001). Mutational signature analyses indicated a common enrichment of DNA mismatch repair-related mutational signatures (SBS3, SBS14, and SBS21) across the RR HNC and PCa models. Transcriptomic profiling revealed an upregulation of the BAHD1 gene, which is involved in heterochromatin formation, across the 4 RR cell lines, corroborated by an enrichment of heterochromatin-related genesets. These results were consistent with functional characterization of RR versus WT cells by WB and IF indicating increased DNA repair capacity and heterochromatin response post-4 Gy irradiation. We further confirmed the dependency of the RR phenotype on the heterochromatin response with BAHD1 knockdown, resulting in reversal of these cellular responses. Finally, our results were supported by survival analyses indicating an inferior DFS post-RT in patients with HNC and PCa harboring a higher expression of heterochromatin-related geneset (HNC: HRhigh vs low 1.51 ; PCa: HRhigh vs low 1.37 ). Conclusions: Herein, by leveraging on paired experimental and clinico-molecular datasets, we have uncovered a novel BAHD1-dependent heterochromatin response that underpins resistance to RT in HNC and PCa, which may be amendable to systemic agents targeting chromatin remodeling.

Clinical, Genomic, and Transcriptomic Characteristics of Patients with Metastatic Renal Cell Carcinoma Who Developed Thromboembolic Events.

Thromboembolic events (TE) are a common complication in patients with metastatic renal cell carcinoma (mRCC) and are associated with poorer clinical outcomes. However, the incidence of TE and clinical and genomic characteristics of patients with mRCC who develop this complication are poorly understood. Herein, we describe the incidence and clinical features of patients with mRCC with or without TE at our institution, and examine their association with the underlying genomic and transcriptomic characteristics of the tumor. This retrospective study included all consecutive cases of mRCC seen at our institution. A CLIA-certified lab performed tumor genomics and transcriptomics. Patients were classified based on the presence of a TE within the first year of diagnosis. Three hundred and seventy patients with mRCC were included in the study. TE was seen in 11% (42) of the patients. Patients with favorable International mRCC Database Consortium (IMDC) risk were less likely to develop a TE. In contrast, patients receiving combination treatment with a tyrosine kinase inhibitor (TKI) and an immune checkpoint inhibitor were more likely to develop a TE. No difference in overall survival among patients with or without TE was observed (52 vs. 55 months; HR 0.85, 95% CI 0.5574-1.293, p = 0.24). The most upregulated pathways in mRCC with TEs versus those without were the xenobiotic metabolism and mTORC1 signaling pathways. Our findings suggest potential biomarkers that, after external validation, could be used to better select patients who would benefit from prophylactic anticoagulation.

HYENA detects oncogenes activated by distal enhancers in cancer.

Somatic structural variations (SVs) in cancer can shuffle DNA content in the genome, relocate regulatory elements, and alter genome organization. Enhancer hijacking occurs when SVs relocate distal enhancers to activate proto-oncogenes. However, most enhancer hijacking studies have only focused on protein-coding genes. Here, we develop a computational algorithm 'HYENA' to identify candidate oncogenes (both protein-coding and non-coding) activated by enhancer hijacking based on tumor whole-genome and transcriptome sequencing data. HYENA detects genes whose elevated expression is associated with somatic SVs by using a rank-based regression model. We systematically analyze 1146 tumors across 25 types of adult tumors and identify a total of 108 candidate oncogenes including many non-coding genes. A long non-coding RNA TOB1-AS1 is activated by various types of SVs in 10% of pancreatic cancers through altered 3-dimensional genome structure. We find that high expression of TOB1-AS1 can promote cell invasion and metastasis. Our study highlights the contribution of genetic alterations in non-coding regions to tumorigenesis and tumor progression.

TG6050, an oncolytic vaccinia virus encoding interleukin-12 and anti-CTLA-4 antibody, favors tumor regression via profound immune remodeling of the tumor microenvironment

BackgroundTG6050 was designed as an improved oncolytic vector, combining the intrinsic properties of vaccinia virus to selectively replicate in tumors with the tumor-restricted expression of recombinant immune effectors to modify...

Faecalibacterium prausnitzii strain EXL01 boosts efficacy of immune checkpoint inhibitors

ABSTRACT Gut microbiota impacts responses to immune checkpoint inhibitors (ICI). A high level of Faecalibacterium prausnitzii have been associated with a positive response to ICI in multiple cancer types. Here, based on fecal shotgun metagenomics data, we show in two independent cohorts of patients with non-small cell lung cancer and advanced melanoma that a high level of F. prausnitzii at baseline is positively associated with a better clinical response to ICI. In MCA205 tumor-bearing mice, administration of F. prausnitzii strain EXL01, already in clinical development for Inflammatory Bowel Disease, restores the anti-tumor response to ICI in the context of antibiotic-induced microbiota perturbation at clinical and tumor transcriptomics level. In vitro, EXL01 strain enhances T cell activation in the presence of ICI. Interestingly, oral administration of EXL01 strain did not induce any change in fecal microbiota diversity or composition, suggesting a direct effect on immune cells in the small intestine. F. prausnitzii strain EXL01 will be evaluated as an adjuvant to ICI in multiple cancers in the near future.

Deciphering Natural Killer Cell Cytotoxicity Against Medulloblastoma in vitro and in vivo: Implications for Immunotherapy.

Medulloblastoma (MB) is the most prevalent paediatric brain tumour. Despite improvements in patient survival with current treatment strategies, the quality of life of these patients remains poor owing to the sequelae and relapse risk. An alternative, or, in addition to the current standard treatment, could be considered immunotherapy, such as Natural Killer cells (NK). NK cells are cytotoxic innate lymphoid cells that play a major role in cancer immunosurveillance. To date, the mechanism of cytotoxicity of NK cells, especially regarding the steps of adhesion, conjugation, cytotoxic granule polarisation in the cell contact area, perforin and granzyme release in two and three dimensions, and therapeutic efficacy in vivo have not been precisely described. Each step of NK cytotoxicity against the three MB cell lines was explored using confocal microscopy for conjugation, Elispot for degranulation, flow cytometry, and luminescence assays for target cell necrosis and lysis and mediators released by cytokine array, and then confirmed in a 3D spheroid model. Medulloblastoma-xenografted mice were treated with NK cells. Their persistence was evaluated by flow cytometry, and their efficacy in tumour growth and survival was determined. In addition, their effects on the tumour transcriptome were evaluated. NK cells showed variable affinities for conjugation with MB target cells depending on their subgroup and cytokine activation. Chemokines secreted during NK and MB cell co-culture are mainly associated with angiogenesis and immune cell recruitment. NK cell cytotoxicity induces MB cell death in both 2D and 3D co-culture models. NK cells initiated an inflammatory response in a human MB murine model by modulating the MB cell transcriptome. Our study confirmed that NK cells possess both in vitro and in vivo cytotoxic activity against MB cells and are of interest for the development of immunotherapy.

Predicting epirubicin response in Danish patients with breast cancer.

539 Background: Anthracyclines are highly effective chemotherapy drugs. However, they are toxic and feared for their cardiotoxicity. There is a need for improved personalized prediction of treatment benefit. For example, state-of-the-art guidelines (NCCN Guidelines Version 1.2024 and meta-analysis PMID: 37061269) mark anthracyclines as optional adjuvant treatment of estrogen receptor (ER) positive, HER2 negative early high-risk breast cancer. A biomarker to predict whether a patient will benefit from anthracycline treatment could potentially lead to increased cure rate and overall reduced toxicity. However, no such test exists. Here we introduce a clinically validated, predictive test based on clinical tumor transcriptome data and the cell line panel NCI60 that can forecast epirubicin response in breast cancer patients with high accuracy. Methods: Microarray gene expression levels and growth inhibition levels (GI50) from the NCI60 cell line panel were acquired from NCBI to build a prediction algorithm. A tumor-specific variance-based filter based on &gt;6.000 patient tumors was applied to select the most relevant genes. AUC (Area Under Curve) was used to evaluate the performance of numerous configurations and combinations of parameters that led to different gene-signature sets. Response scores based on the gene expression level of all genes in each signature were generated for each sample in a published cohort (PMID: 23340299) and a final signature with 141 genes was the best-performing signature (Progressive Disease versus Response AUC 0.81 and ANOVA-test p-value &lt; 0.01). The model was validated on a cohort of Danish breast cancer patients treated with epirubicin in the metastatic setting (n=153), with time-to-progression (TTP) as endpoint (PMID: 31654283, PMID: 30099635). Finally, we used an established method (PMID: 30289602) to test if the gene signature was correlated between microarray- and RNA sequencing-based datasets. Results: The hazard ratio (HR) for the best-performing signature was 0.31 when comparing patients with a difference of at least 50 in response score (two-sided p-value = 0.012, 95% confidence interval 0.12-0.77, endpoint TTP, continuous scoring). This was consistent in a multivariate model including ER and HER2. Using the data and method provided by Pedersen et al (PMID: 30289602), we also saw a high correlation between matching microarray and RNA sequencing datasets for the genes in our model (mean Pearson’s r = 0.87). Conclusions: Here is presented a development and clinical validation of an accurate epirubicin response signature for breast cancer patients. The expression of the genes in the signature is highly correlated between microarray- and RNA sequencing data. Moving forward, we will seek to validate the model independently on RNA sequencing data. Our aim is that these models will be accepted for prospective clinical tests at local hospitals in Denmark in early 2025.

Generalizable transcriptome-based tumor malignant level evaluation and molecular subtyping towards precision oncology

In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients’ prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients’ survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

Comparative analysis of the tumor microbiome, molecular profiles, and immune cell abundances by HPV status in mucosal head and neck cancers and their impact on survival

ABSTRACT Head and Neck Squamous Cell Carcinoma (HNSCC) comprises a diverse group of tumors with variable treatment response and prognosis. The tumor microenvironment (TME), which includes microbiome and immune cells, can impact outcomes. Here, we sought to relate the presence of specific microbes, gene expression, and tumor immune infiltration using tumor transcriptomics from The Cancer Genome Atlas (TCGA) and associate these with overall survival (OS). RNA sequencing (RNAseq) from HNSCC tumors in TCGA was processed through the exogenous sequences in tumors and immune cells (exotic) pipeline to identify and quantify low-abundance microbes. The detection of the Papillomaviridae family of viruses assessed HPV status. All statistical analyses were performed using R. A total of 499 RNAseq samples from TCGA were analyzed. HPV was detected in 111 samples (22%), most commonly Alphapapillomavirus 9 (90.1%). The presence of Alphapapillomavirus 9 was associated with improved OS [HR = 0.60 (95%CI: 0.40–0.89, p = .01)]. Among other microbes, Yersinia pseudotuberculosis was associated with the worst survival (HR = 3.88; p = .008), while Pseudomonas viridiflava had the best survival (HR = 0.05; p = .036). Microbial species found more abundant in HPV- tumors included several gram-negative anaerobes. HPV- tumors had a significantly higher abundance of M0 (p < .001) and M2 macrophages (p = .035), while HPV+ tumors had more T regulatory cells (p < .001) and CD8+ T-cells (p < .001). We identified microbes in HNSCC tumor samples significantly associated with survival. A greater abundance of certain anaerobic microbes was seen in HPV tumors and pro-tumorigenic macrophages. These findings suggest that TME can be used to predict patient outcomes and may help identify mechanisms of resistance to systemic therapies.

Abstract PS18-04: Racial disparities in breast cancer and effect of obesity: MammaPrint, BluePrint and whole transcriptome analyses of tumors in Latin American patients in FLEX trial

Abstract Background: Latin Americans are more likely to be diagnosed with aggressive early-stage breast cancer compared to Non-Hispanic White. Multiple factors may contribute to this, including metabolic factors and ancestry. In a previous study, we identified upregulated immune pathway genes in Luminal B tumors from obese Black patients compared to matched White patients. In this study, we report clinical and transcriptomic profiles of breast tumors from Latin and White patients to enhance understanding of factors contributing to aggressive tumor biology in Latin patients. Methods: We matched 311 Latin and 311 White breast cancer patients enrolled in FLEX by age, T stage, N stage and clinical subtype (ER/PR and HER2 status). FLEX (NCT03053193) is a prospective, observational trial that includes stage I-III breast cancer patients who receive MammaPrint (with or without BluePrint) as standard of care and consent to whole transcriptome and clinical data collection. MammaPrint is a 70-gene risk of distant recurrence signature that classifies patients as Low Risk or High Risk. BluePrint is an 80-gene molecular subtyping signature, categorizes tumors as Luminal-, HER2- or Basal-Type. MammaPrint further groups Luminal into A (Low Risk) and B (High Risk). ImPrint is a 53-gene signature that has been shown to predict the likelihood of achieving pCR with PD1-PDL1 immune checkpoint inhibitors. Statistical analyses on groups were conducted using arsenal R package and p-value &amp;lt; 0.05 was considered significant. Whole transcriptome comparisons were made, using limma R package, between Latin and White patients stratified by BluePrint subtype Luminal and weight categories normal (body-mass-index (BMI) 18.5 to &amp;lt; 25) and obese (BMI ≥30). Significant differentially expressed genes had an adjusted p-value &amp;lt; 0.05. Gene set enrichment analysis (GSEA) was conducted using fgsea R package. Results: Latin patients had significantly higher percentage of type 2 diabetes (23.3% vs 8.5%), BMI obese (49.0% vs 39.4%), BluePrint Basal (14.8% vs 9.3%) and ImPrint Immune Sensitive (12.0% vs 5.1%) compared to matched White patients. When comparing whole transcriptome of tumors from Latin and White patients, only tumors stratified by Luminal B and obesity resulted in differentially expressed genes: Latin patients had higher expression (&amp;gt;2-fold change) of 42 immunoglobulin genes compared to White, with only IGKV6-21 being statistically significant. Additional immune related genes such as IKZF1 and AGER, as well as UTS2 (gene encoding a vasoconstrictor agent and contributor of angiogenesis) were significantly upregulated in Latin patients. Upregulation of immune related pathways such as inflammatory response, interferon alpha/gamma response and downregulation of adipogenesis, oxidative phosphorylation and MYC targets were identified in Latin patients compared to White using GSEA Hallmarks gene sets. Conclusion: There were additional clinical and genomic differences between tumors from Latin and White patients, even when controlling for age, T stage, N stage and clinical subtype. Particularly, there were more type 2 diabetes, BMI obese, BluePrint Basal, and ImPrint Immune Sensitive among Latin patients. In addition, transcriptomic differences between obese Latin and matched White patients were found in Luminal B subgroup that may contribute to the aggressive tumor biology; immunoglobulin genes and immune related pathways were associated with higher expression in Latin patients. This study suggests that biological differences in breast tumors, particularly from obese patients, may result from shared background and reflects the need for inclusion of diverse patient groups in clinical trials. Citation Format: Marcela Mazo-Canola, Virginia Kaklamani, Pooja Advani, Sailaja Kamaraju, Alfredo A. Santillan-Gomez, Robert Maganini, Julie Barone, Sahra Uygun, Lavanya Samraj, William Audeh, Joyce O'Shaughnessy, FLEX Investigators' Group. Racial disparities in breast cancer and effect of obesity: MammaPrint, BluePrint and whole transcriptome analyses of tumors in Latin American patients in FLEX trial [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS18-04.

Abstract RF02-07: Precocious modulation of metabolic and immunological parameters predicts tumor response to fasting-mimicking diet plus chemotherapy in patients with early stage TNBC

Abstract Background: Preclinical studies showed that severely calorie restricted fasting-mimicking diets (FMDs) enhance the antitumor efficacy of chemotherapy (CT) or immunotherapy (IO) in murine triple negative breast cancer (TNBC) models. These effects are mediated by a combination of blood glucose reduction and positive immunomodulatory effects. Moreover, combining fasting and metformin produced synergistic anticancer effects in a broad range of tumor models. The BREAKFAST trial was designed to investigate if FMD, plus/minus metformin, could increase the antitumor activity of neoadjuvant CT in patients with stage I-III TNBC. Methods: BREAKFAST (NCT04248998) is a randomized, non-comparative, phase II, pilot trial that enrolled stage I-III (cT&amp;gt;1 cm) TNBC patients (pts) candidate to receive 4 cycles of neoadjuvant CT with doxorubicin-cyclophosphamide every 3 weeks, followed by 12 cycles of weekly paclitaxel. Pts were randomized 1:1 to receive: CT plus 5-day FMD every 3 weeks, up to 8 cycles (arm A); CT plus FMD plus daily metformin (1700 mg) (arm B). The primary study endpoint was the rate of pCR in either experimental arm. Secondary/exploratory endpoints included safety, compliance, and biomarker analyses based on blood metabolomics and tumor transcriptomics analyses at different timepoints. Results: Between June 2020 and February 2022 we enrolled 30 pts. Then, the study was interrupted after the introduction of chemo-immunotherapy (CT-IO) as a standard neoadjuvant therapy for early stage TNBC pts. Among 30 pts, 13 were treated with CT plus FMD, while 17 pts received CT plus FMD plus metformin. Overall, pCR rate was 56.6%, i.e., significantly higher than pCR rates reported with anthracycline-taxane CT alone in previous phase II/III trials (26-39%), with no significant differences among treatment arms (p=0.49). The FMD acutely reduced blood glucose, insulin and LDH levels, which reflects a reduction in systemic and/or tumor glucose metabolism. Of note, precocious LDH reduction was more pronounced in patients undergoing pCR. RNA-seq analysis of tumor samples revealed a significant downmodulation of glycolysis and TCA cycle pathways after one treatment cycle, paralleled by an increase of intratumor activated T cells, memory T cells and NK cells, as estimated by deconvolution analyses of tumor transcriptomic data. Of note, these changes were observed only in patients achieving pCR. While intratumor metabolic changes were similar in the two treatment arms, the modulation of intratumor immunity was more pronounced in patients not receiving metformin. Conclusion: Preoperative CT plus cyclic FMD (plus/minus metformin) results in excellent pCR rates in localized TNBC patients. Early on-treatment downregulation of systemic and intratumor metabolic parameters related to glucose metabolism predicts pCR, and this is independent of metformin use. Based on results of this study, we recently initiated a large, multicentric trial, namely the BREAKFAST-2 (NCT05763992) study, which will investigate if adding cyclic FMD to neoadjuvant CT-IO increases pCR rates in ~ 145 pts with stage II-III TNBC. Citation Format: Francesca Ligorio, Giovanni Fucà, Andrea Vingiani, Fabio Iannelli, Riccardo Lobefaro, Leonardo Provenzano, Lucrezia Zanenga, Cristina Ferraris, Antonino Belfiore, Silvia Brich, Alessia Bertolotti, Gianfranco Scaperrotta, Catherine Depretto, Antonia Martinetti, Elisa Sottotetti, Paola Antonia Corsetto, Giulia Valeria Bianchi, Giuseppe Capri, Secondo Folli, Saverio Minucci, Marco Foiani, Massimiliano Pagani, Giancarlo Pruneri, Filippo De Braud, Claudio Vernieri. Precocious modulation of metabolic and immunological parameters predicts tumor response to fasting-mimicking diet plus chemotherapy in patients with early stage TNBC [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr RF02-07.

Abstract PS17-01: Key drivers of therapeutic response and resistance to giredestrant from GO39932: a Phase Ia/b study in patients with estrogen receptor-positive, HER2-negative, locally advanced or metastatic breast cancer

Abstract BACKGROUND Several investigational oral selective estrogen receptor antagonists and degraders (SERDs) are under investigation. These were partly developed to benefit patients (pts) with breast cancer (BC) who acquired resistance to standard-of-care (SoC) endocrine therapies (ET); e.g., through gain of ESR1 mutations that enable estrogen-independent ER activity. One such SERD, giredestrant (G), demonstrates activity in pts with ESR1-wild type (WT) or -mutant (m) tumors, and in pts who progressed on other ETs. Results from Phase I/III trials in ER-positive, HER2-negative, locally advanced/metastatic BC (ER+, HER2– LA/mBC) showed that next-generation SERDs had increased activity in ESR1m tumors vs SoC ETs. However, enthusiasm was hindered by heterogeneous responses, driven in part by study design differences. Across acelERA BC (NCT04576455), EMERALD (NCT03778931), SERENA-2 (NCT04214288), and AMEERA-3 (NCT04059484), 30–50% of pts progressed rapidly (&amp;lt; 2 months) when treated with SoC ETs or next-generation SERDs, while others benefited for ≥ 1 year. We present an exploratory biomarker analysis aimed at understanding the mechanistic basis for heterogeneous responses to SERDs in ER+, HER2– LA/mBC, by assessing a Phase Ia/b G cohort (NCT03332797) with paired baseline and on-treatment (tx) biopsies. METHODS Pts had ≤ 2 prior therapies for LA/mBC; disease recurrence/progression while on adjuvant ET for ≥ 24 months and/or ET for ER+, HER2– LA/mBC; and tumor response/stable disease for ≥ 6 months. Single-agent dose-escalation stage: 10, 30, 90, or 250 mg G once daily (QD) on Days (D) 1–28 of 28-D cycles (C). Dose-expansion stage: 30, 100, or 250 mg G QD. 100 mg G + 125 mg palbociclib on a 21-D on/7-D off schedule was also explored. Pre-/perimenopausal pts received LHRH agonists. Paired pre- and on-tx (C2D8) tumor biopsies (n = 29) were immunolabeled for ER, progesterone receptor, and Ki67, and assessed via bulk RNA-sequencing. Pre-tx liquid biopsies (n = 85) were evaluated by FoundationOne Liquid CDx assay. To validate our clinical observations, we generated a SERD-resistant MCF7 cell line and tested its sensitivity to other therapies. RESULTS We compared fast-progressing pts (FP; progression-free survival [PFS] &amp;lt; 2 months) with those experiencing long-term benefit (LTB; PFS &amp;gt; 12 months). LTB was significantly associated with high tumor baseline ER pathway activity. Although the benefit of G was of larger magnitude among pts with ESR1m tumors compared with SoC ET in acelERA BC, here pts with predominantly ESR1WT tumors received LTB on G tx. At the molecular level, G acted on LTB tumors by suppressing cell cycle- and ER-associated genes. In contrast, G had no effect on the transcriptome of FP tumors, which had lower baseline ER activity than LTB tumors. FP tumors were instead enriched for multiple cancer-associated pathways, e.g., RAS/MAPK and PI3K, which may drive resistance to G and thus enable fast progression. By liquid biopsy, most FP pts (&amp;gt; 90%) did not harbor a mutation in the associated pathway (e.g., NF1, KRAS), and thus could not be identified by genomic profiling alone. FP tumors were instead enriched for multiple cancer-associated pathways by gene expression. We explored these mechanisms further in the SERD-resistant cell line, which was similarly enriched for EGFR and MAPK activation vs standard MCF7 cells. Although cells became resistant to ER-targeted drugs, they acquired sensitivity to EGFR/MAPK inhibitors e.g., gefitinib, cobimetinib. CONCLUSIONS We identified molecular features associated with LTB to G and revealed a set of oncogenic pathways associated with FP pts on tx; demonstrating that these pathways represent acquired dependencies and potential therapeutic targets for SERD-resistant tumors and FP pts. Citation Format: Jackson Liang, Christy Ong, Jennifer Giltnane, Junko Aimi, Ching-Wei Chang, Mary Gates, Jennifer Eng-Wong, Pablo Perez-Moreno, Komal Jhaveri, Elgene Lim, Nicholas Turner, Heather Moore. Key drivers of therapeutic response and resistance to giredestrant from GO39932: a Phase Ia/b study in patients with estrogen receptor-positive, HER2-negative, locally advanced or metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS17-01.

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma.

Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.