Gene Expression Signatures Research Articles

Assessing transcriptomic heterogeneity of single-cell RNASeq data by bulk-level gene expression data

BackgroundSingle-cell RNA sequencing (sc-RNASeq) data illuminate transcriptomic heterogeneity but also possess a high level of noise, abundant missing entries and sometimes inadequate or no cell type annotations at all. Bulk-level gene expression data lack direct information of cell population composition but are more robust and complete and often better annotated. We propose a modeling framework to integrate bulk-level and single-cell RNASeq data to address the deficiencies and leverage the mutual strengths of each type of data and enable a more comprehensive inference of their transcriptomic heterogeneity. Contrary to the standard approaches of factorizing the bulk-level data with one algorithm and (for some methods) treating single-cell RNASeq data as references to decompose bulk-level data, we employed multiple deconvolution algorithms to factorize the bulk-level data, constructed the probabilistic graphical models of cell-level gene expressions from the decomposition outcomes, and compared the log-likelihood scores of these models in single-cell data. We term this framework backward deconvolution as inference operates from coarse-grained bulk-level data to fine-grained single-cell data. As the abundant missing entries in sc-RNASeq data have a significant effect on log-likelihood scores, we also developed a criterion for inclusion or exclusion of zero entries in log-likelihood score computation.ResultsWe selected nine deconvolution algorithms and validated backward deconvolution in five datasets. In the in-silico mixtures of mouse sc-RNASeq data, the log-likelihood scores of the deconvolution algorithms were strongly anticorrelated with their errors of mixture coefficients and cell type specific gene expression signatures. In the true bulk-level mouse data, the sample mixture coefficients were unknown but the log-likelihood scores were strongly correlated with accuracy rates of inferred cell types. In the data of autism spectrum disorder (ASD) and normal controls, we found that ASD brains possessed higher fractions of astrocytes and lower fractions of NRGN-expressing neurons than normal controls. In datasets of breast cancer and low-grade gliomas (LGG), we compared the log-likelihood scores of three simple hypotheses about the gene expression patterns of the cell types underlying the tumor subtypes. The model that tumors of each subtype were dominated by one cell type persistently outperformed an alternative model that each cell type had elevated expression in one gene group and tumors were mixtures of those cell types. Superiority of the former model is also supported by comparing the real breast cancer sc-RNASeq clusters with those generated by simulated sc-RNASeq data.ConclusionsThe results indicate that backward deconvolution serves as a sensible model selection tool for deconvolution algorithms and facilitates discerning hypotheses about cell type compositions underlying heterogeneous specimens such as tumors.

Identification of a gene expression signature of vascular invasion and recurrence in stage I lung adenocarcinoma via bulk and spatial transcriptomics.

Microscopic vascular invasion (VI) is predictive of recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but is difficult to assess in resection specimens and cannot be accurately predicted prior to surgery. Thus, new biomarkers are needed to identify this aggressive subset of stage I LUAD tumors. To assess molecular and microenvironment features associated with angioinvasive LUAD we profiled 162 resected stage I tumors with and without VI by RNA-seq and explored spatial patterns of gene expression in a subset of 15 samples by high-resolution spatial transcriptomics (stRNA-seq). Despite the small size of invaded blood vessels, we identified a gene expression signature of VI from the bulk RNA-seq discovery cohort (n=103) and found that it was associated with VI foci, desmoplastic stroma, and high-grade patterns in our stRNA-seq data. We observed a stronger association with high-grade patterns from VI+ compared with VI- tumors. Using the discovery cohort, we developed a transcriptomic predictor of VI, that in an independent validation cohort (n=60) was associated with VI (AUROC=0.86; p=5.42×10-6) and predictive of recurrence-free survival (HR=1.98; p=0.024), even in VI- LUAD (HR=2.76; p=0.003). To determine our VI predictor's robustness to intra-tumor heterogeneity we used RNA-seq data from multi-region sampling of stage I LUAD cases in TRACERx, where the predictor scores showed high correlation (R=0.87, p<2.2×10-16) between two randomly sampled regions of the same tumor. Our study suggests that VI-associated gene expression changes are detectable beyond the site of intravasation and can be used to predict the presence of VI. This may enable the prediction of angioinvasive LUAD from biopsy specimens, allowing for more tailored medical and surgical management of stage I LUAD.

Genome wide-scale CRISPR-Cas9 knockout screens identify a fitness score for optimized risk stratification in colorectal cancer

BackgroundThe molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions.Methodswe systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved.FindingsWe defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate.InterpretationThe CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.

Multi-cohort analysis reveals immune subtypes and predictive biomarkers in tuberculosis

Tuberculosis (TB) remains a significant global health threat, necessitating effective strategies for diagnosis, prognosis, and treatment. This study employs a multi-cohort analysis approach to unravel the immune microenvironment of TB and delineate distinct subtypes within pulmonary TB (PTB) patients. Leveraging functional gene expression signatures (Fges), we identified three PTB subtypes (C1, C2, and C3) characterized by differential immune-inflammatory activity. These subtypes exhibited unique molecular features, functional disparities, and cell infiltration patterns, suggesting varying disease trajectories and treatment responses. A neural network model was developed to predict PTB progression based on a set of biomarker genes, achieving promising accuracy. Notably, despite both genders being affected by PTB, females exhibited a relatively higher risk of deterioration. Additionally, single-cell analysis provided insights into enhanced major histocompatibility complex (MHC) signaling in the rapid clearance of early pathogens in the C3 subgroup. This comprehensive approach offers valuable insights into PTB pathogenesis, facilitating personalized treatment strategies and precision medicine interventions.

Deciphering novel molecular gene expression signatures and pathways in cystic fibrosis through integrative bioinformatics strategies

Cystic fibrosis (CF), a fatal autosomal recessive disorder, is triggered by a genetic alteration of the CF transmembrane conductance regulator (CFTR) gene. On a global scale, around one in 3000 live births are affected with CF annually. While diagnosis and therapy are available for CF patients with non-specific and rare mutations, the current research is dedicated to exploring customized biomarkers, genes, signaling networks, and therapy for improving the management of CF. Although still in the early stages of development and validation, mRNA and gene-based treatment strategies are aimed to target patients who are resistant to CFTR gene restoration therapies. In this study, we utilized the systems biology approaches integrated with gene expression analysis to identify novel biomarkers and pathways for CF treatment. At first, out of 54,676 differentially expressed genes, we identified 104 upregulated and 107 downregulated genes. The upregulated genes were largely concentrated on Glutamatergic synapses, and the downregulated genes were enriched in ubiquitin-mediated proteolysis. Utilizing the enrichment analysis, we explored deeper into the pathways linked to these genes, with emphasis on relevant pathways involving bronchial epithelial cells. Following the enrichment analysis, we identified six essential genes: WWP2, RNASEL, CUL1, CDC42, HDAC4, and UBA2. Furthermore, the discovered genes were evaluated using expression profile analysis. Finally, our data indicate that the WWP2 gene has a critical role in CF management. The current findings provide a coherent theoretical foundation for future experiments to further explore the WWP2 gene as a unique and prognostic target for developing an effective CF therapeutic approach.

Prelude to malignancy: A gene expression signature in normal mammary gland from breast cancer patients suggests pre-tumorous alterations and is associated with adverse outcomes.

Despite advances in early detection and treatment strategies, breast cancer recurrence and mortality remain a significant health issue. Recent insights suggest the prognostic potential of microscopically healthy mammary gland, in the vicinity of the breast lesion. Nonetheless, a comprehensive understanding of the gene expression profiles in these tissues and their relationship to patient outcomes remain missing. Furthermore, the increasing trend towards breast-conserving surgery may inadvertently lead to the retention of existing cancer-predisposing mutations within the normal mammary gland. This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling, followed by whole-transcriptome verification experiments and statistical analyses to discern molecular signatures and their clinical relevance. A distinct gene expression signature was identified in uninvolved mammary gland samples, featuring key cellular components encoding keratins, CDH1, CDH3, EPCAM cell adhesion proteins, matrix metallopeptidases, oncogenes, tumor suppressors, along with crucial genes (FOXA1, RAB25, NRG1, SPDEF, TRIM29, and GABRP) having dual roles in cancer. Enrichment analyses revealed disruptions in epithelial integrity, cell adhesion, and estrogen signaling. This signature, named KAOS for Keratin-Adhesion-Oncogenes-Suppressors, was significantly associated with reduced tumor size but increased mortality rates. Integrating molecular assessment of non-malignant mammary tissue into disease management could enhance survival prediction and facilitate personalized patient care.

Artificial intelligence-based epigenomic, transcriptomic and histologic signatures of tobacco use in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) biomarker studies rarely employ multi-omic biomarker strategies and pertinent clinicopathologic characteristics to predict mortality. In this study we determine for the first time a combined epigenetic, gene expression, and histology signature that differentiates between patients with different tobacco use history (heavy tobacco use with ≥10 pack years vs. no tobacco use). Using The Cancer Genome Atlas (TCGA) cohort (n = 257) and an internal cohort (n = 40), we identify 3 epigenetic markers (GPR15, GNG12, GDNF) and 13 expression markers (IGHA2, SCG5, RPL3L, NTRK1, CD96, BMP6, TFPI2, EFEMP2, RYR3, DMTN, GPD2, BAALC, and FMO3), which are dysregulated in OSCC patients who were never smokers vs. those who have a ≥ 10 pack year history. While mortality risk prediction based on smoking status and clinicopathologic covariates alone is inaccurate (c-statistic = 0.57), the combined epigenetic/expression and histologic signature has a c-statistic = 0.9409 in predicting 5-year mortality in OSCC patients.

MITOCHONDRIAL ANTIVIRAL PATHWAYS CONTROL ANTI-HIV RESPONSES AND ISCHEMIC STROKE OUTCOMES VIA THE RIG-1 SIGNALING AND INNATE IMMUNITY MECHANISMS.

Occludin (ocln) is one of the main regulatory cells of the blood-brain barrier (BBB). Ocln silencing resulted in alterations of the gene expression signatures of a variety of genes of the innate immunity system, including IFN-stimulated genes (ISGs) and the antiviral retinoic acid-inducible gene-1 (RIG-1) signaling pathway, which functions as a regulator of the cytoplasmic sensors upstream of the mitochondrial antiviral signaling protein (MAVS). Indeed, we observed dysfunctional mitochondrial bioenergetics, dynamics, and autophagy in our system. Alterations of mitochondrial bioenergetics and innate immune protection translated into worsened ischemic stroke outcomes in EcoHIV-infected ocln deficient mice. Overall, these results allow for a better understanding of the molecular mechanisms of viral infection in the brain and describe a previously unrecognized role of ocln as a key factor in the control of innate immune responses and mitochondrial dynamics, which affect cerebral vascular diseases such as ischemic stroke.

Clinically unfavorable transcriptome subtypes of non-WNT/non-SHH medulloblastomas are associated with a predominance in proliferating and progenitor-like cell subpopulations.

The non-WNT/non-SHH (Grp3/Grp4) medulloblastomas (MBs) include eight second-generation subgroups (SGS; I-VIII) each with distinct molecular and clinical characteristics. Recently, we also identified two prognostically relevant transcriptome subtypes within each SGS MB, which are associated with unique gene expression signatures and signaling pathways. These prognostic subsets may be in connection to the intra-tumoral cell landscape that underlies SGS MB clinical-molecular diversity. Here, we performed a deconvolution analysis of the Grp3/Grp4 MB bulk RNA profiles using the previously identified single-cell RNA-seq reference dataset and focusing on variability in the cellular composition of SGS MB. RNA deconvolution analysis of the Grp3/Grp4 MB disclosed the subgroup-specific neoplastic cell subpopulations. Neuronally differentiated axodendritic GP3-C1 and glutamatergic GP4-C1 subpopulations were distributed within Grp3- and Grp4-associated SGS MB, respectively. Progenitor GP3-B2 subpopulation was prominent in aggressive SGS II MB, whereas photoreceptor/visual perception GP3/4-C2 cell content was typical for SGS III/IV MB. The current study also revealed significant variability in the proportions of cell subpopulations between clinically relevant SGS MB transcriptome subtypes, where unfavorable cohorts were enriched with cell cycle and progenitor-like cell subpopulations and, vice versa, favorable subtypes were composed of neuronally differentiated cell fractions predominantly. A higher than median proportion of proliferating and progenitor cell subpopulations conferred the shortest survival of the Grp3 and Grp 4MB, and similar survival associations were identified for all SGS MB except SGS IV MB. In summary, the recently identified clinically relevant Grp3/Grp4 MB transcriptome subtypes are composed of different cell populations. Future studies should aim to validate the prognostic and therapeutic role of the identified Grp3/Grp4 MB inter-tumoral cellular heterogeneity. The application of the single-cell techniques on each SGS MB separately could help to clarify the clinical significance of subgroup-specific variability in tumor cell content and its relation with prognostic transcriptome signatures identified before.

Characterization of patient-derived intestinal organoids for modelling fibrosis in Inflammatory Bowel Disease

Background and aimsIntestinal fibrosis is a common complication of Inflammatory Bowel Disease (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC), but the precise mechanism by which it occurs is incompletely understood hampering the development of effective therapeutic strategies. Here, we aimed at inducing and characterizing an inflammation-mediated fibrosis in patient-derived organoids (PDOs) issued from crypts isolated from colonic mucosal biopsies of IBD pediatric patients and age matched-control subjects (CTRLs).MethodsInflammatory-driven fibrosis was induced by exposing CTRL-, CD- and UC-PDOs to the pro-inflammatory cytokine TNF-α for one day, followed by a co-treatment with TNF-α and TGF-β1 for three days. Fibrotic response was proven by analyzing inflammatory and fibrotic markers by RT-qPCR and immunofluorescence. Transcriptomic changes were assessed by RNA-sequencing.ResultsCo-treatment with TNF-α and TGF-β1 caused in CTRL- and IBD-PDOs morphological changes towards a mesenchymal-like phenotype and up-regulation of inflammatory, mesenchymal, and fibrotic markers. Transcriptomic profiling highlighted that in all intestinal PDOs, regardless of the disease, the co-exposure to TNF-α and TGF-β1 regulated EMT genes and specifically increased genes involved in positive regulation of cell migration. Finally, we demonstrated that CD-PDOs display a specific response to fibrosis compared to both CTRL- and UC-PDOs, mainly characterized by upregulation of nuclear factors controlling transcription.ConclusionsThis study demonstrates that intestinal PDOs may develop an inflammatory-derived fibrosis thus representing a promising tool to study fibrogenesis in IBD. Fibrotic PDOs show increased expression of EMT genes. In particular, fibrotic CD-PDOs display a specific gene expression signature compared to UC and CTRL-PDOs.

Specialized Tfh cell subsets driving type-1 and type-2 humoral responses in lymphoid tissue

Effective antibody responses are essential to generate protective humoral immunity. Different inflammatory signals polarize T cells towards appropriate effector phenotypes during an infection or immunization. Th1 and Th2 cells have been associated with the polarization of humoral responses. However, T follicular helper cells (Tfh) have a unique ability to access the B cell follicle and support the germinal center (GC) responses by providing B cell help. We investigated the specialization of Tfh cells induced under type-1 and type-2 conditions. We first studied homogenous Tfh cell populations generated by adoptively transferred TCR-transgenic T cells in mice immunized with type-1 and type-2 adjuvants. Using a machine learning approach, we established a gene expression signature that discriminates Tfh cells polarized towards type-1 and type-2 response, defined as Tfh1 and Tfh2 cells. The distinct signatures of Tfh1 and Tfh2 cells were validated against datasets of Tfh cells induced following lymphocytic choriomeningitis virus (LCMV) or helminth infection. We generated single-cell and spatial transcriptomics datasets to dissect the heterogeneity of Tfh cells and their localization under the two immunizing conditions. Besides a distinct specialization of GC Tfh cells under the two immunizations and in different regions of the lymph nodes, we found a population of Gzmk+ Tfh cells specific for type-1 conditions. In human individuals, we could equally identify CMV-specific Tfh cells that expressed Gzmk. Our results show that Tfh cells acquire a specialized function under distinct types of immune responses and with particular properties within the B cell follicle and the GC.

Biomarker analysis and updated clinical outcomes: Neoadjuvant systemic treatment (NST) with nivolumab (nivo) and relatlimab (rela) in surgically resectable melanoma.

9587 Background: NST with immune checkpoint blockade (ICB) improves clinical outcomes over upfront surgery followed by adjuvant treatment (tx) in patients (pts) with stage III, surgically resectable melanoma. The NST platform also provides an opportunity for deep translational analysis to identify baseline (BL) biomarkers predicting pathologic response and to gain insights into resistance. BL biomarkers, including gene expression signatures (GES) such as IFN-γ/ tumor mutational burden, tumor infiltrating lymphocytes, and presence of tertiary lymphoid structures, have been associated with pathologic response to NST with anti-PD1 and/or anti-CTLA4 antibodies. These studies have not evaluated the newest ICB combination, nivo (anti-PD1) + rela (anti-LAG3), which achieved a major pathologic response rate (MPR) (≤10% viable tumor) of 63% in a Ph II study (NCT02519322). Here we report GES analysis from BL and longitudinal tumor tissues obtained on this study and correlations with outcomes. Methods: Longitudinal tissue was collected from 30 pts treated on the clinical trial and available RNA analyzed using the NanoString nCounter PanCancer IO360 panel. Clinical outcomes, including recurrence and event-free survival, were also updated with longer follow-up. Pts were grouped into MPR and non- major pathologic responders (non MPR). Normalization, differential expression / GES evaluation was performed using nSolver Advanced Analysis software. Differential expression is fit on a per signatures basis using a linear model for analysis. P-values were adjusted within each analysis and on the grouping variable level difference t-test using the Benjamini and Yekutieli False Discovery Rate adjustment to account for correlations amongst the tests. BL analysis was grouped based on pathologic response, MPR vs non-MPR. Results: Of the 30 pts (median follow up 44 months), 53 RNA samples from 26 patients (9 NR and 17 R) were included in the full analysis. Immune GES with significantly higher (adjusted p&lt; 0.05) differences at BL in MPR vs non-MPR included: B cells, CD45, CD-8+ T cells, TIGIT, IDO1, and IFN-γ. Significantly higher B7-H3 GES at BL was associated with non MPR. Additional analyses (i.e., cell population changes over time) and association with event outcomes are underway. Conclusions: To our knowledge, this is the first longitudinal RNA analysis reported from pts treated with nivo+rela. BL immune features associated with major pathologic response include higher GES of B cells, CD45+ cells, CD8 T cells, and increased expression of TIGIT, IDO and IFN-y. Additionally, higher B7-H3 in non MPR pts may indicate a clinically actionable strategy for further evaluation. Ongoing analyses of longitudinal samples and correlations with clinical outcomes are underway and will be presented. Clinical trial information: NCT02519322 .

RNA-Seq based gene expression profiling of baseline and on-treatment breast tumors to predict response to HER2-directed therapy, without chemotherapy (TBCRC026).

530 Background: Robust biomarkers are needed to personalize treatment in early stage HER2-positive breast cancer. The TBCRC026 trial (n=83) demonstrated that early metabolic changes on FDG-PET/CT [&gt;40% decline in SULmax at day 15 post treatment initiation (C1D15); C1D15 SULmax] were associated with response to neoadjuvant trastuzumab/pertuzumab (HP), without chemotherapy, in an ER-negative, HER2-positive cohort (NCT01937117). We investigated the association of RNA sequencing (RNAseq)-based gene expression signatures (GES) at baseline and on-treatment (C1D15), with early metabolic change on PET/CT and clinical outcomes. Methods: RNAseq (664 GES) was performed on baseline (n=56) and C1D15 (n=31) tumor biopsies (25 paired samples available). Association with pCR following HP (secondary), PET/CT parameters and survival (exploratory) was studied. Gene expression changes between baseline and C1D15 samples were tested by Wilcoxon signed-rank test. Association between GES and PET/CT parameters and GES with pCR were evaluated using logistic regression models. Cox regressions were performed to study the association between PET/CT SULmax at C1D15 and a B cell signature and relapse-free survival (RFS). The likelihood ratio test was used to compare the prognostic ability of two nested Cox models. Results: Both RNAseq and clinical outcomes were available in 53/83 patients. HER2-enriched (HER2-E) intrinsic subtype comprised 71% (40/56) of cases at baseline and 61% (19/31) at D15; basal subtype for 27% (15/56) and 39% (12/31), respectively. pCR rate was 19% (10/53) with all but one exhibiting HER2-E subtype. One basal-like sample underwent pCR, with downregulation of HER2 amplicon and IgG signatures slightly more prominent. Gene expression changes from baseline to C1D15 were analyzed; ERBB2was downregulated after HP (p = 0.007), B cell signatures, CD4, CD8, natural killer cells and Treg cells were significantly upregulated at C1D15. GES associated with 40% decline in SULmax at C1D15 included ERBB2 amplicon genes ( ERBB2, GRB7) and correlation to the HER2-E subtype, whereas basal-like signatures were significantly associated with lack of response on PET at C1D15. Univariate logistic regression analysis suggested that FOS-JUN, fibroblast and B cell GES at baseline were significantly associated with pCR (p=&lt;0.05). Finally, the addition of a B cell signature improved the prognostic value of C1D15 SULmax on PET/CT for RFS (p &lt; 0.05). Conclusions: In this unique cohort with ER-negative, HER2-positive breast cancer treated with neoadjuvant HP without chemotherapy, HER2-E tumors and those with increased immune signaling were more likely to respond to HER2-directed therapy. Combining C1D15 SULmax on PET/CT and a B cell signature provided improved prognostic information and should be further explored as candidate biomarkers in this setting. Clinical trial information: NCT01937117 .

A high throughput cell stretch device for investigating mechanobiology in vitro

Mechanobiology is a rapidly advancing field, with growing evidence that mechanical signaling plays key roles in health and disease. To accelerate mechanobiology-based drug discovery, novel in vitro systems are needed that enable mechanical perturbation of cells in a format amenable to high throughput screening. Here, both a mechanical stretch device and 192-well silicone flexible linear stretch plate were designed and fabricated to meet high throughput technology needs for cell stretch-based applications. To demonstrate the utility of the stretch plate in automation and screening, cell dispensing, liquid handling, high content imaging, and high throughput sequencing platforms were employed. Using this system, an assay was developed as a biological validation and proof-of-concept readout for screening. A mechano-transcriptional stretch response was characterized using focused gene expression profiling measured by RNA-mediated oligonucleotide Annealing, Selection, and Ligation with Next-Gen sequencing. Using articular chondrocytes, a gene expression signature containing stretch responsive genes relevant to cartilage homeostasis and disease was identified. The possibility for integration of other stretch sensitive cell types (e.g., cardiovascular, airway, bladder, gut, and musculoskeletal), in combination with alternative phenotypic readouts (e.g., protein expression, proliferation, or spatial alignment), broadens the scope of high throughput stretch and allows for wider adoption by the research community. This high throughput mechanical stress device fills an unmet need in phenotypic screening technology to support drug discovery in mechanobiology-based disease areas.

Integrated genomic and transcriptomic characterization of neuroendocrine carcinomas for improved treatment decision-making.

e15138 Background: Neuroendocrine carcinomas (NECs) are poorly characterized due to their innate heterogeneity, thus limiting treatment and clinical trial options for patients. Here, we used whole exome sequencing (WES) and RNA sequencing (RNA-seq) to explore the genetic and microenvironmental landscape of NECs in order to understand the unique features of different NEC types, with the aim of improving treatment modalities. Methods: We analyzed 51 NEC clinical samples morphologically verified by a pathologist: lung NEC (20 small cell NEC and 1 large cell NEC cases), gastroenteropancreatic NEC (GEP, 12 cases), cancer of unknown primary (7 cases), Merkel cell carcinoma (MCC, 5 cases), genitourinary tract NEC (3 cases), and breast NEC (3 cases). Findings on tumor mutational burden (TMB, mut/Mb), microsatellite instability (MSI), gene expression signatures, and tumor microenvironment (TME) profiling were reported. Small cell lung cancer (SCLC) subtyping was performed as reported by Gay et al. on the entire NEC cohort. Results: Half of the patients with lung NEC and 84% of those with extrapulmonary NEC satisfied the molecular inclusion criteria for clinical trials, with the most frequent criterion being KRAS G12X or G13X mutations. Among the extrapulmonary NEC samples, 13.7% were deemed eligible for targeted therapy, specifically for cases with BRAF V600E mutation and/or high TMB (&gt; 10 mut/Mb). We detected varying TMB and distinct gene expression features across the entire cohort. Specifically, we found 2 MCC cases to be Merkel cell polyomavirus-positive with low TMB and devoid of UV-associated mutations. One GEP-NEC case exhibited a high MSI (MSI-high) status. We detected 6 SCLC cases (3 non-smokers, 3 former smokers) with surprisingly low levels of tobacco-associated mutations (&lt;10% of all mutations). Two GEP-NEC cases had high levels of mutations associated with tobacco smoking. While TME profiling showed no significant difference in cell population makeup across all samples, transcriptional SCLC subtyping revealed significant differences among the cases. Inflammatory SCLC (SCLC-I) samples showed statistically significant enrichment of all subpopulations of the immune microenvironment (i.e., B cells, T cells, NK cells), supporting the use of immune checkpoint blockade for treatment. The POU2F3+ SCLC (SCLC-P) samples showed low expression of all neuroendocrine diagnostic markers (i.e., INSM1, NCAM1, SYP, CHGA). Conclusions: Given the heterogeneous molecular features across diverse NEC tumors, a uniform treatment strategy is unlikely to benefit all NEC patients. Hence, our ability to detect these unique molecular features is crucial for matching individual NEC patients with specific clinical trials and targeted therapies that may improve their outcomes. Thus, a concerted effort using in-depth genomic, transcriptomic, and TME profiling for NEC tumors is warranted.

Evaluating tumor inflammation and PD-L1 expression in sequential biopsies of real-world primary and metastatic breast cancer.

e13035 Background: Biomarkers for measuring immunogenicity of tumors such as PD-L1 immunohistochemistry (IHC), tumor mutational burden (TMB), and immune gene expression have been studied in many cancers including breast cancer. How these biomarkers change over time and how their detection differs with sequential testing in the real-world clinical setting has been studied to a lesser extent but is an important consideration for optimal patient care. Methods: We performed an analysis of 30 patients with primary and metastatic breast cancer sequentially tested by comprehensive genomic and immune profiling (CGIP) at two time points during routine clinical care to observe temporal changes in immunotherapy markers and immune gene expression. Genomic variants and TMB were assessed with DNA-seq, while immune gene expression was assessed with RNA-seq. PD-L1 expression was determined using IHC. Immune gene expression signatures characterizing the tumor microenvironment (TME) were calculated, including tumor inflammation (TIGS), cell proliferation (CP), and cancer testis antigen burden (CTAB). Differences between sequential tests were tested for using linear mixed effect models. Results: Time between biopsies for sequential tests ranged from the same day to 4.5 years, with 40% of specimens being collected within 30 days of the first. Sequential specimens were collected from breast (27%), non-breast (40%), or a mix of breast and non-breast (33%) tissue. Non-breast tissue types included sites from lymph node (18%), GI tract (15%), skin (10%), thorax (7%), and musculoskeletal sites (7%). Overall, TMB, PD-L1 IHC, and gene expression signatures were relatively stable between sequential tests (P &gt; 0.05); however, trends were noted for second tests detecting lower tumor inflammation (TIGS score) and PD-L1 IHC (P = 0.1). Further, second tests detected significantly lower levels of tumor inflammation when both were performed on non-breast tissue (P = 0.04), but not when performed on all breast (P = 0.7) or a mix of breast and non-breast (P = 0.6) tissues. An opposite trend was noted for PD-L1 where second tests detected lower levels of PD-L1 IHC when both tests were performed on breast tissue (P = 0.1), but not when performed on all non-breast (P = 0.4) or a mix of breast and non-breast (P = 0.5) tissue. Tissue-dependent trends were still present even when excluding lymph node specimens (P = 0.1). Conclusions: Changes in immunotherapy markers and immune gene expression signatures, on average, remained relatively stable over time, except for tumor inflammation and PD-L1 IHC when sequentially testing all non-breast or breast tissue, respectively. These observations highlight the utility of clinical CGIP testing in revealing temporal changes of the TME, which may help inform clinical trial or treatment strategies occurring over time for primary and metastatic breast cancer.

Biological subgroups in melanoma: A correlation of tumor genomic and transcriptomic analysis with spatial immunophenotyping.

e14667 Background: A prominent challenge advancing immunotherapy is the heterogeneity of resistance mechanisms leading to drug development failure despite efficacy in subgroup of patients. To address these shortcomings, precision medicine platforms aimed at prospectively stratifying patients into treatment groups based on tumor mutational burden (TMB) and tumor inflammation scores by gene expression profiling (GEP) are now being explored. Whether these gene-based variables reflect the true immunologic state of the tumor remains an open question. Here, we sought to evaluate TMB and GEP as markers of intratumoral inflammatory state by single-cell spatial analysis. Methods: Under an IRB approved protocol through the Huntsman Cancer Institute, 25 melanoma tumors with available clinical, WES, and RNAseq data were stained with a multiplex immunofluorescence-based protocol using Opal dye and Leica Bond Rx (CD8, CD68, PD1, PD-L1, Ki67, SOX10, DAPI) and scanned with Akoya Polaris whole slide scanner. Images were analyzed using HALO. Results: Melanoma tumors were stratified into 4 subgroups based on TMB (&lt;10 vs ≥10 m/Mb) by WES, and inflammatory (Inflm) gene signature expression (GSEA &gt;0 vs ≤0) by RNAseq, denoted as S1 (TMBhi/Inflmhi; n=4), S2 (TMBhi/Inflmlo; n=4), S3 (TMBlo/Inflmhi; n=8), and S4 (TMBlo/Inflmlo; n=9). The rate of disease progression was 0% (S1), 25% (S2), 25% (S3), and 56% (S4). Infiltration analysis of CD8 T cells showed elevated intratumoral CD8 density in S1 (249/mm2) and S3 (157/mm2) vs S2 (65/mm2) and S4 (65/mm2; p=0.0002), consistent with GEP findings. Spatial analysis showed a similar pattern of CD8 distribution across subgroups with peak CD8 density in the tumor periphery. Proximity analyses showed average distance of CD8 T cell to the nearest tumor cell was not different across subgroups. Furthermore, we found Inflmhi tumors had a higher frequency of PD1+ CD8 T cells relative to Inflmlo tumors (12.9 vs 2.8 cells/HPF; p=0.0002), suggesting GEP also reflects CD8 activation and functional status. Increased frequency of PD1+ CD8 T cells was correlated with a much improved overall survival (HR=3.3; p=0.017). A similar analysis performed on CD68+ macrophages showed significantly increased peri-tumoral macrophage recruitment in S4 (445/mm2) vs S1 (209/mm2; p&lt;0.0001), S2 (91/mm2; p&lt;0.0001), and S3 (267/mm2; p=0.0003) subgroups. Interestingly, Inflmhi tumors were associated with an increased proportion of PDL1+ macrophages regardless of TMB status (43% vs 3%; p&lt;0.0001), suggestive of an upregulated adaptive immune response in tumors with active inflammation. Conclusions: Our findings illustrate that biological groupings based on TMB and GEP biomarkers correlate with CD8 spatial location and activation state. Each subgroup has unique tumor immune features that can be related to immune resistance and warrant further investigation.

GOG 3088: A randomized phase II study of letrozole versus observation in patients with newly diagnosed uterine leiomyosarcoma.

TPS5643 Background: Uterine leiomyosarcomas (uLMS) are rare, accounting for less than five percent of all malignant uterine neoplasms. Approximately 85% of women present with clinical stage I disease (i.e., disease limited to the uterus and cervix). NCCN guidelines for stage I uterine confined disease currently recommend observation; however, recurrence risk of uLMS overall is quite high at 50-70% within the first two years. The estrogen receptor (ER) is expressed in 40-87% of leiomyosarcomas. Because of this high expression, estrogen may act as a growth factor that stimulates cell proliferation and tumor growth. Subsequently, there have been several evaluations for the use of aromatase inhibitors as single agent therapy for uLMS. These trials have each shown varying degrees of clinical activity. We hypothesize that by decreasing systemic estrogen using an aromatase inhibitor we will prolong the time to recurrence for patients with this disease. Methods: This is a GOG Foundation led phase II randomized controlled trial comparing letrozole (2.5mg PO daily) to observation in newly diagnosed patients with uterine confined stage I uLMS. Forty patients will be randomized 1:1. Patients will be eligible post operatively if they have no measurable disease and will be required to be estrogen receptor (ER) positive, as defined by ³ 10% expression by immunohistochemistry (IHC). No stratification methods will be applied. The primary endpoint of the trial is investigator-assessed progression free survival. Exploratory translational evaluation will occur to 1) correlate response to letrozole based on IHC hormone receptor status, 2) evaluate gene expression signatures of hormone receptor activity, tumor biology, and tumor microenvironment in relation to response to letrozole, and 3) evaluate the contribution of single nucleotide polymorphism rs3820282 to tumor biology and response to letrozole. GOG 3088 activated in January of 2024 and expects to enroll across 20 US sites. Clinicaltrials.gov Identifier: NCT05649956. Clinical trial information: NCT05649956 .

Association of androgen receptor gene expression signature and ARV7with clinical outcome in metastatic hormone-sensitive prostate cancer.

Association of androgen receptor gene expression signature and <i>ARV7</i>with clinical outcome in metastatic hormone-sensitive prostate cancer.

Interaction between VEGF-A and immune checkpoint targets in triple-negative breast cancer and mechanisms of immune evasion and tumor progression.

1096 Background: Immune checkpoint inhibitors (ICIs) have revolutionized the treatment triple negative breast cancer (TNBC). However, not all patients with TNBC benefit from the addition of ICIs due to factors such as intrinsic and acquired resistance to ICIs, and complex interplay between tumor and immune cells in the tumor microenvironment (TME). Vascular endothelial growth factor (VEGF) promotes angiogenesis and potentially modulates tumor immune evasion. A phase I clinical trial has shown that a bispecific antibody to VEGF-A and PD-L1 produces encouraging tumor responses in advanced TNBC. In this study, we investigated the interaction between VEGF and various immune gene expression signatures including PD-L1 in a real-world breast cancer patient population. Methods: Comprehensive immune profiling, including the RNA-seq based gene expression assessment of 395 immune-associated genes, was performed on 120 formalin-fixed paraffin-embedded breast cancer samples. PD-L1 expression (Combined Positive Score, CPS ≥ 10%) was measured by immunohistochemistry (IHC; 22C3). Clinicopathologic variables were collected. Statistical associations between quantitative biomarkers, including 28 immune checkpoint genes, were calculated using Pearson correlations (r), and comparisons of quantitative biomarkers between groups were performed using the proportions test. For statistical significance, p&lt;0.05 was required. Results: The study cohort included 29 patients (24.2%) with TNBC and 91 (75.2%) with non-TNBC (including ER+/HER2- and HER2+). Most patients had metastatic tumors (n=92, 76.7%) and invasive ductal carcinoma (n=83, 69.2%). Among the TNBC group, 21 patients had PD-L1 positive tumors (72.4%), defined by CPS ≥ 10.In non-TNBC, VEGF has significant, though weak (r&lt;0.35) correlations with the expression of three checkpoint genes: AKT1 (r=0.35, p=0.00063), ICOS (r=0.34, p=0.00099), and TIM3 (r=0.29, p=0.0061). In TNBC, VEGF has significant, strong (r&gt;0.47) correlations with the expression of three other checkpoint genes: PD-1 (r=0.47, p=0.0094), PD-L1 (r=0.57, p=0.0012), and PIK3CA (r=0.6, p=0.00051) However, in TNBC, VEGF gene expression does not have a statistical association with PD-L1 IHC (CPS ≥/&lt; 10 (p=0.9)). Conclusions: Our findings suggest that there is an interplay between angiogenesis and an immunosuppressive tumor immune microenvironment in TNBC to a greater degree than in non-TNBCs. This supports the notion that angiogenesis mediators such as VEGF-A may enhance the expression of immunosuppressive checkpoint molecules, leading to immune evasion and tumor progression. Combination treatments of ICIs, especially anti-PD-1 therapy, with VEGF antibodies may be promising approaches to enhance the immune responses in TNBC, especially in tumors with CPS&lt;10, where the current frontline treatment is cytotoxic chemotherapy.