Expression Signatures Research Articles

Epithelial cell states associated with kidney and allograft injury.

The kidney epithelium, with its intricate arrangement of highly specialized cell types, constitutes the functional core of the organ. Loss of kidney epithelium is linked to the loss of functional nephrons and a subsequent decline in kidney function. In kidney transplantation, epithelial injury signatures observed during post-transplantation surveillance are strong predictors of adverse kidney allograft outcomes. However, epithelial injury is currently neither monitored clinically nor addressed therapeutically after kidney transplantation. Several factors can contribute to allograft epithelial injury, including allograft rejection, drug toxicity, recurrent infections and postrenal obstruction. The injury mechanisms that underlie allograft injury overlap partially with those associated with acute kidney injury (AKI) and chronic kidney disease (CKD) in the native kidney. Studies using advanced transcriptomic analyses of single cells from kidney or urine have identified a role for kidney injury-induced epithelial cell states in exacerbating and sustaining damage in AKI and CKD. These epithelial cell states and their associated expression signatures are also observed in transplanted kidney allografts, suggesting that the identification and characterization of transcriptomic epithelial cell states in kidney allografts may have potential clinical implications for diagnosis and therapy.

Molecular features and prognostic factors of locally advanced microsatellite instability-high gastric cancer.

Microsatellite instability-high (MSI-H) tumors are distinct molecular subtypes in gastric cancer. However, a few studies have comprehensively reported the molecular features of MSI-H tumors and their prognostic factors in locally advanced gastric cancer. This study aimed to clarify the molecular features and prognostic factors of locally advanced MSI-H gastric cancer. This study included 499 patients with locally advanced gastric cancer who underwent radical gastrectomy. We evaluated the MSI status and compared with previously published whole-exome sequencing, panel sequencing, and gene expression profiling data. Clinicopathological characteristics and molecular profiles were compared between patients with MSI-H and microsatellite stable (MSS) gastric cancer. A subgroup analysis of survival was performed in patients with MSI-H gastric cancer. MSI-H tumors were detected in 79 of 499 patients (15.8%). MSI-H tumors were associated with an increased tumor mutational burden, MLH1 downregulation, CD274 (PD-L1) upregulation, and enrichment of cell cycle pathways. Among patients with MSI-H gastric cancer, the disease-specific survival (DSS) tended to be better in the surgery plus tegafur, gimeracil, and oteracil potassium (S-1) adjuvant chemotherapy group than in the surgery alone group, especially for stage III patients. Furthermore, DSS was better in the T cell-inflamed gene expression signature-high group, and it tended to be worse in the non-solid type poorly differentiated adenocarcinoma group. The molecular features and prognostic factors of locally advanced MSI-H gastric cancer were clarified. S-1 adjuvant chemotherapy appears to be beneficial, and the T cell-inflamed gene expression signature and histopathological type are prognostic factors in MSI-H tumors.

Transcriptome deconvolution reveals absence of cancer cell expression signature in immune checkpoint blockade response.

Immune-checkpoint therapy (ICB) has conferred significant and durable clinical benefit to some cancer patients. However, most patients do not respond to ICB, and reliable biomarkers of ICB response are needed to improve patient stratification. Here, we performed a transcriptome-wide meta-analysis across 1,486 tumors from ICB-treated patients and tumors with expected ICB outcomes based on microsatellite status. Using a robust transcriptome deconvolution approach, we inferred cancer and stroma-specific gene expression differences and identified cell-type specific features of ICB response across cancer types. Consistent with current knowledge, stromal expression of CXCL9, CXCL13, and IFNG were the top determinants of favorable ICB response. In addition, we identified a group of potential immune-suppressive genes, including FCER1A, associated with poor response to ICB. Strikingly, PD-L1 expression in stromal cells, but not cancer cells, is correlated with ICB response across cancer types. Furthermore, the unbiased transcriptome-wide analysis failed to identify cancer-cell intrinsic expression signatures of ICB response conserved across tumor types, suggesting that cancer cells lack tissue-agnostic transcriptomic features of ICB response.

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

Intestinal 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). Inflammatory-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. Co-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. This 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.

CREB5 as an essential transcription and tumorigenic regulator in basal-like breast and prostate cancer.

1107 Background: Breast cancers (BC) harbor basal-like transcriptional profiles, in which a large subset are pathologically triple negative breast cancers (TNBC). These are hormone therapy insensitive, have limited targeted therapies, and decreased overall survival (OS). Recent studies determined that prostate cancers (PCs) also exhibit luminal- or basal-like transcriptional subtypes. The 30-40% of basal-like PCs exhibit resistance to hormone therapies and have overall worse clinical outcomes. Here we deployed in silico computational models and tumor phenotype testing in vitro and in vivo. This identified that CREB5, a transcription factor commonly amplified or overexpressed in advanced cancers, regulates basal-like BCs and PCs through stem cell-like genes and properties that drive tumor formation. Methods: Protein and RNA levels were examined in 5 subtypes of BC from the TCGA (n=981). Normalized expression and PAM50 signatures were analyzed using data from Decipher tests of PC patients (n=585). Kaplan-Meier curves were used to compare relapse free survival in PC (n=84) and OS in TNBC (n=248). The ALAN (Algorithm for Linking Activity Networks (1) computational tool was used to determine gene-gene similarities of ~20,000 genes based on ~400,000,000 pairwise comparisons in 208 tumors. In PC (LNCaP) and TNBC (MDA-MB-231 and HCC1806) cell lines, we examined gene expression profiles from RNA-seq and found Hallmark signatures through Gene Set Enrichment Analysis. Motif analysis was conducted from ChIP-seq data on immuno-precipitated CREB5. We conducted in vitro and in vivo assessment of tumorigenicity. Results: Basal BCs harbored increased CREB5 expression and CREB5-high basal BCs had worse outcomes (HR 2.09, 95% CI 1.1-3.96, p<0.021). Reflecting this, in basal-like BC cell lines, CREB5 increased cell viability and formation of tumor-like spheroids in 3D culture. In PCs, CREB5 had a positive correlation with basal- and not luminal-like PCs (Spearman ρ = 0.519, p<0.001). Through ALAN analysis of metastatic PCs, CREB5 exhibited strong concordance with other known resistance genes (FGFR1/2) as well as transcription factors that promote stem cell-like features. Particularly, CREB5 was associated with increased FOSL1 (Spearman ρ = 0.37, p<0.001), a metastasis-regulating gene. In PC cell lines, CREB5 overexpression promoted FOSL1 and other stem cell-like genes and co-bound to FOSL1 transcription regulatory elements. CREB5 overexpression in PC cell lines promoted the formation of tumor-like colonies, spheroids, and increased tumor formation from the xenografts in mice. Conclusions: Basal-like BCs and PCs demonstrate overexpression of CREB5, a gene that promotes tumor formation and stem cell-like genes. This mechanistic knowledge may guide treatment management strategies and aid in the development of novel therapies against basal-like BCs and PCs. 1. Bergom et al, Communications Biology, 2023.

Transcriptome-based response predictor to identify potential responders among patients with negative standard markers for response to immune checkpoint blockers.

2666 Background: Immune checkpoint blockers (ICB) are revolutionizing cancer treatment, and are being approved for an increasingly wide range of cancer types. The most common biomarkers currently in use to select patients for ICB are PD-L1 expression on tumor cells, as measured by IHC, and tumor mutational burden (TMB) and microsatellite instability (MSI), both measured by NGS. However, some patients that are negative for these markers still respond to ICB. This calls for complementary biomarkers to better identify responders to ICB, especially in patients that are negative to current biomarkers. Here, we focus on predicting response to anti-PD1 in patients with negative PD-L1, TMB or MSI. Methods: We employ ENLIGHT, our transcriptome-based precision oncology platform, which identifies and utilizes clinically relevant genetic interactions to predict a patient’s response to a wide range of targeted drugs, including ICB. ENLIGHT generates an individual ICB response score calculated from a 10-gene expression signature - the ENLIGHT Matching Score (EMS). Patients with EMS above a predetermined threshold are considered matched by ENLIGHT to anti-PD-1 treatments. We have previously shown, based on more than 1000 cases analyzed retrospectively, that this signature can identify responders to anti-PD-1 with high accuracy. Here, we use ENLIGHT to perform a retrospective analysis of 125 cases from three different datasets, who had low PD-L1 presentation (<1%), low TMB (< 10) or microsatellite stable tumors (MSS), and were treated with anti-PD-1, to specifically assess ENLIGHT’s performance in this biomarker-negative sub-population. Results: Patients who responded to anti-PD-1 treatments had significantly higher EMS in all three datasets. Correspondingly, ENLIGHT is highly predictive of response to anti-PD-1 in patients with negative ICB markers in the three datasets (ROC AUCs of 0.80, 0.84, 0.77, respectively, for low PDL1, low TMB and MSS). It is important to note that ENLIGHT was not trained on any of these datasets, and is applied as-is using previously published parameters. Overall, we find that patients who are ENLIGHT-Matched to anti-PD1 in this biomarker-negative cohort are almost 3 times more likely to respond than patients who are not (31% vs. 11%, p=5e-13). Conclusions: ENLIGHT is a powerful tool for predicting response to anti-PD-1 treatment in patients with negative standard biomarkers for ICB, a currently unmet need with considerable clinical importance.

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<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<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>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 ≥/< 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<10, where the current frontline treatment is cytotoxic chemotherapy.

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 [>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=<0.05). Finally, the addition of a B cell signature improved the prognostic value of C1D15 SULmax on PET/CT for RFS (p < 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 .

IκBα controls dormancy in hematopoietic stem cells via retinoic acid during embryonic development

Recent findings suggest that Hematopoietic Stem Cells (HSC) and progenitors arise simultaneously and independently of each other already in the embryonic aorta-gonad mesonephros region, but it is still unknown how their different features are established. Here, we uncover IκBα (Nfkbia, the inhibitor of NF-κB) as a critical regulator of HSC proliferation throughout development. IκBα balances retinoic acid signaling levels together with the epigenetic silencer, PRC2, specifically in HSCs. Loss of IκBα decreases proliferation of HSC and induces a dormancy related gene expression signature instead. Also, IκBα deficient HSCs respond with superior activation to in vitro culture and in serial transplantation. At the molecular level, chromatin regions harboring binding motifs for retinoic acid signaling are hypo-methylated for the PRC2 dependent H3K27me3 mark in IκBα deficient HSCs. Overall, we show that the proliferation index in the developing HSCs is regulated by a IκBα-PRC2 axis, which controls retinoic acid signaling.

Development of a multiparametric prognostic score based on PAM50, in patients with HR+/HER2- advanced breast cancer (aBC) treated with endocrine therapy (ET) plus cyclin dependent kinase 4 and 6 inhibitors (CDKi), within the CDK-PREDICT (SOLTI-1801) study and HCB cohort.

1061 Background: CDKi + ET combinations have demonstrated efficacy in improving progression-free survival (PFS) and overall survival (ribociclib) in HR+/HER2- aBC in the first-line setting. Intrinsic subtypes (IS) are prognostic and predict benefit from CDKi + ET. The multiparametric PAM50MET score has demonstrated prognostic value prior to the widespread use of CDKi in HR+/HER2- aBC patients. Here we developed a new prognostic score based on PAM50 assay from metastatic baseline biopsies prior to CDKi + ET within the CDK-PREDICT (SOLTI-1801) study and the Hospital Clinic de Barcelona (HCB) cohort. Methods: RNA from FFPE tumors was analyzed at the nCounter (Nanostring Technologies) using a 72 custom gene panel including the PAM50 genes. Intrinsic subtyping (luminal A, luminal B, HER2-enriched, basal-like, and normal-like) was performed using the research-based PAM50 IS predictor. The following parameters were used to develop the predictive score: PAM50 subtype assignments, PAM50 subtype expression signatures (PAM50 scores), expression of 72 individual genes included in the custom panel (PAM50 and no PAM50 genes) and 14 clinical variables. Parameters were assessed individually and all in combination. The most parsimonious model with the highest Harrel C-index (C-index) was selected. The prognostic value of the new model was assessed using multivariable Cox regression models (adjusting by endocrine sensitivity, visceral disease, and de novo metastatic disease) as a continuous variable and as a categorical variable. Results: Between May 2020 and May 2022, 185 patients (113 from CDK-PREDICT study and 72 from HCB cohort) diagnosed with HR+/HER2- aBC were evaluated. The combined model (CDK-SCORE) that achieved the highest C-index (table) included 4 clinical variables (ECOG, liver metastases, progesterone receptor expression and Ki-67), 6 genes as a continuous variable (AR, BRCA1, CCND1, CCNE1, PGR and FGFR4) and HER2-enriched and basal-like subtypes PAM50 scores. CDK-SCORE as a continuous variable was associated with PFS (aHR: 2.77, 95% CI 2.12 – 3.61). The median PFS of CDK-SCORE LOW patients was 32.9 months (95% CI 23.3 – NA) vs 16.3 months (95% CI 12.1 – 19.7) in CDK-SCORE HIGH patients (aHR: 2.76, 95% CI 1.74 – 4.37). CDK-SCORE was also categorised by tertiles and quartiles and mPFS and Kaplan-Meier curves will be presented. Conclusions: The combined CDK-SCORE demonstrates prognostic value in patients diagnosed with HR+/HER2- aBC and treated with ET+CDKi in the first-line setting. Future plans include conducting an external validation of the CDK-SCORE. [Table: see text]

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 (> 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 (<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.

Tumour-associated myeloid cells expressing IL-10R2/IL-22R1 as a potential biomarker for diagnosis and recurrence of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a poor survival rate, largely due to the lack of early diagnosis. Although myeloid cells are crucial in the tumour microenvironment, whether their specific subset can be a biomarker of PDAC progression is unclear. We analysed IL-22 receptor expression in PDAC and peripheral blood. Additionally, we analysed gene expression profiles of IL-10R2+/IL-22R1+ myeloid cells and the presence of these cells using single-cell RNA sequencing and murine orthotropic PDAC models, respectively, followed by examining the immunosuppressive function of IL-10R2+/IL-22R1+ myeloid cells. Finally, the correlation between IL-10R2 expression and PDAC progression was evaluated. IL-10R2+/IL-22R1+ myeloid cells were present in PDAC and peripheral blood. Blood IL-10R2+ myeloid cells displayed a gene expression signature associated with tumour-educated circulating monocytes. IL-10R2+/IL-22R1+ myeloid cells from human myeloid cell culture inhibited T cell proliferation. By mouse models for PDAC, we found a positive correlation between pancreatic tumour growth and increased blood IL-10R2+/IL-22R1+ myeloid cells. IL-10R2+/IL-22R1+ myeloid cells from an early phase of the PDAC model suppressed T cell proliferation and cytotoxicity. IL-10R2+ myeloid cells indicated tumour recurrence 130 days sooner than CA19-9 in post-pancreatectomy patients. IL-10R2+/IL-22R1+ myeloid cells in the peripheral blood might be an early marker of PDAC prognosis.

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 > 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.

Neuroanatomical, transcriptomic, and molecular correlates of math ability and their prognostic value for predicting learning outcomes.

Foundational mathematical abilities, acquired in early childhood, are essential for success in our technology-driven society. Yet, the neurobiological mechanisms underlying individual differences in children's mathematical abilities and learning outcomes remain largely unexplored. Leveraging one of the largest multicohort datasets from children at a pivotal stage of knowledge acquisition, we first establish a replicable mathematical ability-related imaging phenotype (MAIP). We then show that brain gene expression profiles enriched for candidate math ability-related genes, neuronal signaling, synaptic transmission, and voltage-gated potassium channel activity contributed to the MAIP. Furthermore, the similarity between MAIP gene expression signatures and brain structure, acquired before intervention, predicted learning outcomes in two independent math tutoring cohorts. These findings advance our knowledge of the interplay between neuroanatomical, transcriptomic, and molecular mechanisms underlying mathematical ability and reveal predictive biomarkers of learning. Our findings have implications for the development of personalized education and interventions.

Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles

Individual may response to drug treatment differently due to their genetic variants located in enhancers. These variants can alter transcription factor’s (TF) binding strength, affect enhancer’s chromatin activity or interaction, and eventually change expression level of downstream gene. Here, we propose a computational framework, PERD, to Predict the Enhancers Responsive to Drug. A machine learning model was trained to predict the genome-wide chromatin accessibility from transcriptome data using the paired expression and chromatin accessibility data collected from ENCODE and ROADMAP. Then the model was applied to the perturbed gene expression data from Connectivity Map (CMAP) and Cancer Drug-induced gene expression Signature DataBase (CDS-DB) and identify drug responsive enhancers with significantly altered chromatin accessibility. Furthermore, the drug responsive enhancers were related to the pharmacogenomics genome-wide association studies (PGx GWAS). Stepping on the traditional drug-associated gene signatures, PERD holds the promise to enhance the causality of drug perturbation by providing candidate regulatory element of those drug associated genes.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

MRNA-lncRNA gene expression signature in HPV-associated neoplasia and cervical cancer

mRNA-lncRNA gene expression signature in HPV-associated neoplasia and cervical cancer

Right ventricular outflow tract cardiomyocytes possess distinct calcium handling and contractile properties

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): Rembrandt Research Grant 2021 Background The right ventricular outflow tract (RVOT) is the predominant site of origin of idiopathic ventricular tachycardia. Idiopathic ventricular tachycardias are typically sensitive to adenosine, consistent with triggered activity caused by delayed afterdepolarizations due to intracellular Ca2+ overload. The distinct properties of RVOT myocytes explaining increased susceptibility to Ca2+ overload and triggered activity are unknown. Purpose To identify distinct RVOT electrophysiological properties including Ca2+ handling and its molecular underpinnings. Methods and Results Experiments were performed using freshly isolated cardiomyocytes from the RVOT and right ventricular (RV) apex of adult rabbit hearts. To identify distinct RVOT electrophysiological properties, we employed the perforated patch clamp methodology and measured action potentials and L-type Ca2+ current. Action potentials of RVOT myocytes were significantly shorter compared to RV myocytes, particularly at lower pacing frequency. L-type Ca2+ current peak density was significantly lower in RVOT myocytes compared to RV myocytes (34.0 ± 9.1% at 0 mV). However, voltage-dependencies of L-type Ca2+ current activation and inactivation were not statistically different. Next we measured intracellular Ca2+ transients using the fluorescent Ca2+ indicator indo-1 and found that Ca2+ transient amplitudes were significantly lower in RVOT myocytes compared to RV myocytes. To investigate a relationship between RVOT myocyte Ca2+ handling and contractility, we performed unloaded sarcomere shortening measurements using the Cytocypher Multicell system. Shortening of relaxation time following increased pacing frequency (1-2 Hz) was significantly larger for RVOT myocytes compared to RV myocytes. To identify molecular factors explaining the distinct properties of RVOT myocytes, we performed RNA-seq analysis of differential gene expression using the DESeq2 method. RVOT and RV transcriptomic profiles consisted of 30 differentially expressed genes (adjusted p ≤ 0.05). One of genes significantly higher expressed by the RV was synaptotagmin (SYT1), a Ca2+ sensor and positive regulator of the cardiac L-type Ca2+ channel through inhibition of syntaxin 1A [Ref. 1, 2]. Conclusion RVOT cardiomyocytes possess distinct electrophysiological and contractile properties, reflected by shorter action potentials, lower Ca2+ transient amplitudes, and larger shortening of relaxation time upon increasing pacing frequency. The RVOT and RV have similar but distinct gene expression signatures. Future experiments will focus on determining the role of SYT1 and other genes in regulation of the L-type Ca2+ current and Ca2+ handling in RVOT myocytes.Distinct properties of RVOT myocytes.Transcriptomic profile of the RVOT.

Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD

Accurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr−/−.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.