Gene Expression Score Research Articles

Canonical TGF-\u03b2 signaling regulates the relationship between prenatal maternal depression and amygdala development in early life

Canonical transforming growth factor-beta (TGF-β) signaling exerts neuroprotection and influences memory formation and synaptic plasticity. It has been considered as a new target for the prevention and treatment of depression. This study aimed to examine its modulatory role in linking prenatal maternal depressive symptoms and the amygdala volumes from birth to 6 years of age. We included mother–child dyads (birth: n = 161; 4.5 years: n = 131; 6 years: n = 162) and acquired structural brain images of children at these three time points. Perinatal maternal depressive symptoms were assessed using the Edinburgh Postnatal Depression Scale (EPDS) questionnaire to mothers at 26 weeks of pregnancy and 3 months postpartum. Our findings showed that the genetic variants of TGF-β type I transmembrane receptor (TGF-βRI) modulated the association between prenatal maternal depressive symptoms and the amygdala volume consistently from birth to 6 years of age despite a trend of significance at 4.5 years of age. Children with a lower gene expression score (GES) of TGF-βRI exhibited larger amygdala volumes in relation to greater prenatal maternal depressive symptoms. Moreover, children with a lower GES of the TGF-β type II transmembrane receptor (TGF-βRII), Smad4, and Smad7 showed larger amygdala volumes at 6 years of age in relation to greater prenatal maternal depressive symptoms. These findings support the involvement of the canonical TGF-β signaling pathway in the brain development of children in the context of in utero maternal environment. Such involvement is age-dependent.

Analysis of the role of Frizzled 2 in different cancer types.

Frizzled 2 (FZD2) is an important receptor in the Wnt pathway, which is highly expressed in malignant tumors and helps regulate multiple tumor behaviors. Its expression level is related to prognosis. Here, bioinformatic analysis was performed to understand the expression of FZD2 in different tumors. We examined FZD2 expression using pan‐cancer data of 33 cancer types from The Cancer Genome Atlas (TCGA). Differential expression analysis (Wilcoxon's test) was used to compare tumor and normal tissues. Univariate Cox proportional hazard regression was performed to compare gene expression and overall patient survival. COSMIC, cBioPortal, and CCLE were used to examine FZD2 mutations in human cancers. Dryness index was calculated using one‐class logistic regression (OCLR). Spearman's correlation was performed based on gene expression and dryness score and used to analyze the correlation between gene expression and stemness score, matrix score, immune score, estimated score, tumor mutation burden (TMB), microsatellite instability (MSI), and drug sensitivity. STRING website was used to construct an FZD2 protein interaction network and identify genes that interact with FZD2. We report that FZD2 is highly expressed in most tumors, differing between cancer types. Expression was related to patient overall survival (OS), disease‐specific survival, disease‐free interval (DFI), mutations, drug sensitivity, tumor microenvironment, immune cell infiltration, immune checkpoint gene expression, immunotherapy indicators (TMB, MSI), and tumor cell stemness. FZD2 influenced drug sensitivities, including cobimetinib (r = −0.553, P < 0.001), selumetinib (r = −0.539, P < 0.001), bafetinib (r = −0.538, P < 0.001), tamoxifen (r = −0.523, P < 0.001), alvespimycin (r = −0.520, P < 0.001), and nilotinib (r = −0.502, P < 0.001). FZD2 has the most significant correlation with ROR2 (r = 0.4, P < 0.001), Wnt2 (r = 0.37, P < 0.001), and Wnt4A (r = 0.34, P < 0.001). The results confirm the importance of FZD2 expression in cancer prognosis and treatment, and provide new clues for treatment strategies.

Integrated clinicopathologic and molecular risk stratification for disease recurrence in muscle-invasive bladder cancer.

490 Background: Integrating molecular subtypes, gene transcripts associated with disease recurrence (DR), and clinicopathologic features may help risk stratify muscle-invasive bladder cancer (MIBC) patients &amp; guide therapy selection. We hypothesized that combined transcriptomic &amp; clinical data would improve risk stratification for DR (local or distant) after cystectomy +/- adjuvant chemotherapy. Methods: We identified 401 MIBC patients (pT2-4 N0-N3 M0) in The Cancer Genome Atlas with detailed demographic, clinical, pathologic, and treatment-related data. We split the data into training (60%) &amp; testing (40%) sets. We produced RNA gene expression scores for molecular subtype using 48 established, relevant genes (PMID 28988769). In the training set, we performed feature selection by conducting random forest modeling of an additional 108 genes associated with DR. We kept genes of highest importance based on the evaluation of increasing mean-squared error &amp; node purity. We excluded highly correlated genes &amp; used the false discovery rate method for multiple hypotheses testing. We performed univariable analyses on genes of highest importance, molecular subtype, &amp; clinicopathologic variables. Using adjusted multivariable analyses (MVA), we built two models: with &amp; without transcriptomic data. Using the testing set, we compared the final models' performance to predict DR, using receiver operating characteristics &amp; area under the curve (AUC). Results: Median follow-up was 18 months (range 1-168). 104 patients recurred with a 5-yr cumulative incidence of 34.6%[28.6-40.5%]. Using the training set, we identified 6 genes significantly associated with DR (VEGFA, TRMT1, FGFR2B, ERBB2, MMP14, PDGFC). The final MVA showed that the new 6-gene signature (HR 1.61, 95% CI 1.27-2.05, p &lt; 0.001); immune molecular subtype [increased expression of PD-L1, PD-1, IDO1, CXCL11, L1CAM, SAA1] (HR 0.52, 95% CI 0.29-0.94, p = 0.03); smoking status (HR 1.17 per 10 pack-years, 95% CI 1.05-1.29, p = 0.005); and local failure risk factors [≥pT3 with negative margins &amp; ≥10 nodes removed (HR 1.63, 95% CI 1.15-2.32, p = 0.006); ≥pT3 and positive margins OR &lt; 10 nodes removed (HR 3.26, 95%CI 2.43 to 4.09, p = 0.007)], were all significantly associated with DR. This combined model outperformed a stand-alone clinicopathologic model (AUC 0.75 vs. 0.66) in the testing set. The combined model stratified patients based on DR risk into 3 groups with 5-yr cumulative incidences of 19.8%[7.7-31.9%] (low-risk); 34.5%[26.1-42.8%] (intermediate); and 49.8%[37.7-61.9%] (high), Gray’s Test p &lt; 0.0001. Conclusions: To our knowledge, this study is the first to integrate clinicopathologic &amp; transcriptomic information (including molecular subtype) to better stratify MIBC patients by risk of recurrence. This stratification may help guide decision-making for adjuvant treatment. Further validation is warranted.

Abstract PS6-11: Targetable ERBB2 mutation status is an independent marker of adverse prognosis in estrogen receptor positive, ERBB2 non-amplified primary lobular breast carcinoma: Validation using a novel gene signature of HER2 activation

Abstract Invasive lobular carcinoma (ILC) accounts for 10-15% of primary breast cancer and is typically ER+ and ERBB2 non-amplified. There is preclinical evidence that somatic ERBB2 mutation may provide an alternative and tractable mechanism for upregulation of HER2 activity in tumors that do not express HER2 by current clinical criteria. Using large public datasets, we previously demonstrated that targetable ERBB2 mutations are enriched in ILC versus invasive ductal carcinoma (IDC) and are an independent prognostic factor in ILC (HR=3.7, 95% CI 1.2-11.0; p=0.021)*. We next hypothesized that a gene expression signature incorporating HER2 activity due to ERBB2 mutation and / or amplification would validate the prognostic signal we found in ILC. To derive a novel gene expression signature of HER2 activity that accounted for the effect of potentially targetable ERBB2 mutations in ERBB2 non-amplified tumors, we applied a weighted average difference method to gene expression data in cases from the METABRIC 2012 (N=1,980) and TCGA 2015 (N=817) cohorts. To compare our novel gene expression signature with an established signature of HER2 activity, we performed multivariate regression modeling of response to neratinib, a small molecule tyrosine kinase inhibitor of HER1, 2 and 4, using pharmacogenomic data accessed via the CellMinerCDB online portal. We show that our novel HER2 pathway signature score uniquely enriches for ERBB2 mutated tumors. Using a Cox regression model and stratifying gene expression scores into upper versus lower quartiles, we were able to validate the prognostic signal of ERBB2 mutations in ILC tumors (HR for 10-year OS in ILC=2.3, 95% CI 1.04-5.05; p=0.040). In contrast, no relationship was found between ERBB2 mutation status or novel HER2 pathway enrichment score and patient outcome in cases of IDC. We conclude that ERBB2 mutations that are enriched in ILC provide a robust biomarker of HER2 pathway activation and can be detected via gene expression signature. Novel clinical trials of HER2-targeted therapy in ERBB2 non-amplified primary ILC are warranted. *Reference: Kurozumi S et al, Cancer Research 2019, 80(4) suppl: SABCS 2019 Abstract P1-18-06 and medRxiv 2020.01.24.20018622 Citation Format: Mansour Alsaleem, Sasagu Kurozumi, Kartikeya Bhardwaj, Cintia Monteiro, Stacey EP Joosten, Andrew R Green, Takaaki Fujii, Ken Shirabe, Ian O Ellis, Emad A Rakha, Nigel P Mongan, David M Heery, Wilbert Zwart, Steffi Oesterreich, Simon J Johnston. Targetable ERBB2 mutation status is an independent marker of adverse prognosis in estrogen receptor positive, ERBB2 non-amplified primary lobular breast carcinoma: Validation using a novel gene signature of HER2 activation [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS6-11.

Exploration of biomarkers from a pilot weight management study for men undergoing radical prostatectomy

BackgroundSeveral biologic mechanisms, including inflammation and immune changes, have been proposed to explain the role of obesity in prostate cancer (CaP) progression. Compared to men of a healthy weight, overweight and obese men are more likely to have CaP recurrence post-prostatectomy. Obesity is related to inflammation and immune dysregulation; thus, weight loss may be an avenue to reduce inflammation and reverse these immune processes. ObjectivesThis study explores the reversibility of the biological mechanisms through intentional weight loss using a comprehensive weight management program in men undergoing prostatectomy. Outcomes include blood and tissue biomarkers, microtumor environment gene expression, inflammation markers and Dietary Inflammatory Index (DII) scores. MethodsTwenty overweight men undergoing prostatectomy participated in this study. Fifteen men chose the intervention and 5 men chose the nonintervention group. The intervention consisted of a comprehensive weight loss program prior to prostatectomy and a weight maintenance program following surgery. Prostate tissue samples were obtained from diagnostic biopsies before the intervention and prostatectomy samples after weight loss. Blood samples and diet records were collected at baseline, pre-surgery after weight loss and at study end after weight maintenance. Immunohistochemistry and NanoString analysis were used to analyze the tissue samples. Flow cytometry was used to assess circulating immune markers. Inflammation markers were measured using Luminex panels. ResultsThe intervention group lost >5% body weight prior to surgery. DII scores improved during the weight loss intervention from baseline to pre-surgery (P = 0.002); and between group differences were significant (P = 0.02). DII scores were not associated with IL-6 nor hsCRP. In the intervention, CXCL12, CXCR7, and CXCR4 (C-X-C motif chemokine ligand/receptor) and Ki67 expression decreased in the prostate tissue from biopsy to surgery (P = 0.06), yet plasma CXCL12 increased during the same timeframe (P = 0.009). The downregulation of several genes (FDR<0.001) was observed in the intervention compared to the non-intervention. Changes in immune cells were not significant in either group. ConclusionThis feasibility study demonstrates that in overweight men with localized CaP, weight loss alters blood, and tissue biomarkers, as well as tumor gene expression. More research is needed to determine the biological and clinical significance of these findings.

Icb-1 expression inhibits growth and fulvestrant response of breast cancer cells and affects survival of breast cancer patients.

Human gene icb-1 recently has been reported to be part of a gene expression score predicting response to antiestrogen fulvestrant in breast cancer patients. In the present study, we examined to what extent icb-1 expression would affect the response of breast cancer cells to this antiestrogen in vitro and investigated underlying molecular mechanisms. Using open access mRNA data, we elucidated the significance of icb-1 expression for survival of breast cancer patients. Icb-1 gene expression was knocked down by RNAi. Breast cancer cell growth after treatment with fulvestrant was assessed using the Cell Titer Blue assay. Gene expression was analyzed by Western blot analysis or RT-qPCR. Survival analyses were performed using bioinformatical online tools and data. Knockdown of icb-1 in T-47D breast cancer cells significantly increased growth of this cell line and also elevated the growth-stimulatory effect of E2 (p < 0.001). After treatment with different concentrations of fulvestrant, icb-1 knockdown cells exhibited a significantly enhanced response to this drug (p < 0.01). On the molecular level, icb-1 knockdown led to elevated expression of ESR1 and its target gene TFF1 (pS2) and enhanced E2-triggered up-regulation of proliferation genes. Finally, bioinformatical meta-analysis of gene expression data of 3951 breast cancer patients revealed that high icb-1 expression increases their relapse-free survival (HR = 0.87, p < 0.05). The presented data further support a tumor-suppressive role of icb-1 in breast cancer and suggest an inhibitory effect of this gene on fulvestrant action, which both are suggested to be mediated by suppression of cellular E2 response.

Hot-Melt Extrusion: An Emerging Technique for Solubility Enhancement of Poorly Water-Soluble Drugs.

The solubility of the drug is a significant aspect to be considered during manufacturing of pharmaceutical products. Poor aqueous solubility of drugs imparts depleted bioavailability. In this regard, several techniques are available for enhancing drug solubility or dissolution. However, only few of them are scalable and industrially applicable. Hot-melt extrusion (HME) is one such technique that has been widely used in the industry. It is a single-step, continuous manufacturing, and scalable method that has proved successful in improving the solubility of poorly soluble drugs. This review highlights the numerous pharmaceutical applications of HME, such as formulations of sterile implants, taste masking of unpleasant drugs, cocrystallization, salt formation, sustained and controlled release formulations, etc. It also describes various hydrophilic and hydrophobic carriers utilized in HME. This review also briefly discusses the recent advances in HME and gives an update on the currently available marketed products. The opportunities and challenges in future development of pharmaceutical products by HME technique are also discussed.

Leveraging gene expression subgroups to classify DLBCL patients and select for clinical benefit from a novel agent

AbstractDiffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, commonly described by cell-of-origin (COO) molecular subtypes. We sought to identify novel patient subgroups through an unsupervised analysis of a large public dataset of gene expression profiles from newly diagnosed de novo DLBCL patients, yielding 2 biologically distinct subgroups characterized by differences in the tumor microenvironment. Pathway analysis and immune deconvolution algorithms identified higher B-cell content and a strong proliferative signal in subgroup A and enriched T-cell, macrophage, and immune/inflammatory signals in subgroup B, reflecting similar biology to published DLBCL stratification research. A gene expression classifier, featuring 26 gene expression scores, was derived from the public dataset to discriminate subgroup A (classifier-negative, immune-low) and subgroup B (classifier-positive, immune-high) patients. Subsequent application to an independent series of diagnostic biopsies replicated the subgroups, with immune cell composition confirmed via immunohistochemistry. Avadomide, a CRL4CRBN E3 ubiquitin ligase modulator, demonstrated clinical activity in relapsed/refractory DLBCL patients, independent of COO subtypes. Given the immunomodulatory activity of avadomide and the need for a patient-selection strategy, we applied the gene expression classifier to pretreatment biopsies from relapsed/refractory DLBCL patients receiving avadomide (NCT01421524). Classifier-positive patients exhibited an enrichment in response rate and progression-free survival of 44% and 6.2 months vs 19% and 1.6 months for classifier-negative patients (hazard ratio, 0.49; 95% confidence interval, 0.280-0.86; P = .0096). The classifier was not prognostic for rituximab, cyclophosphamide, doxorubicin, vincristine, prednisone or salvage immunochemotherapy. The classifier described here discriminates DLBCL tumors based on tumor and nontumor composition and has potential utility to enrich for clinical response to immunomodulatory agents, including avadomide.

Data mining of immune-related prognostic genes in metastatic melanoma microenvironment.

Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune‐related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune‐related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune‐related biomarkers for metastatic melanoma.

TP53 Abnormalities Correlate with Immune Infiltration and Associate with Response to Flotetuzumab Immunotherapy in Acute Myeloid Leukemia

TP53 Abnormalities Correlate with Immune Infiltration and Associate with Response to Flotetuzumab Immunotherapy in Acute Myeloid Leukemia

A Rejection Gene Expression Score in Indication and Surveillance Biopsies Is Associated with Graft Outcome.

Rejection-associated gene expression has been characterized in renal allograft biopsies for cause. The aim is to evaluate rejection gene expression in subclinical rejection and in biopsies with borderline changes or interstitial fibrosis and tubular atrophy (IFTA). We included 96 biopsies. Most differentially expressed genes between normal surveillance biopsies (n = 17) and clinical rejection (n = 12) were obtained. A rejection-associated gene (RAG) score was defined as its geometric mean. The following groups were considered: (a) subclinical rejection (REJ-S, n = 6); (b) borderline changes in biopsies for cause (BL-C, n = 13); (c) borderline changes in surveillance biopsies (BL-S, n = 12); (d) IFTA in biopsies for cause (IFTA-C, n = 20); and (e) IFTA in surveillance biopsies (IFTA-S, n = 16). The outcome variable was death-censored graft loss or glomerular filtration rate decline ≥ 30 % at 2 years. A RAG score containing 109 genes derived from normal and clinical rejection (area under the curve, AUC = 1) was employed to classify the study groups. A positive RAG score was observed in 83% REJ-S, 38% BL-C, 17% BL-S, 25% IFTA-C, and 5% IFTA-S. A positive RAG score was an independent predictor of graft outcome from histological diagnosis (hazard ratio: 3.5 and 95% confidence interval: 1.1–10.9; p = 0.031). A positive RAG score predicts graft outcome in surveillance and for cause biopsies with a less severe phenotype than clinical rejection.

TP53 abnormalities correlate with immune infiltration and associate with response to flotetuzumab immunotherapy in AML

AbstractSomatic TP53 mutations and 17p deletions with genomic loss of TP53 occur in 37% to 46% of acute myeloid leukemia (AML) with adverse-risk cytogenetics and correlate with primary induction failure, high risk of relapse, and dismal prognosis. Herein, we aimed to characterize the immune landscape of TP53-mutated AML and determine whether TP53 abnormalities identify a patient subgroup that may benefit from immunotherapy with flotetuzumab, an investigational CD123 × CD3 bispecific dual-affinity retargeting antibody (DART) molecule. The NanoString PanCancer IO360 assay was used to profile 64 diagnostic bone marrow (BM) samples from patients with TP53-mutated (n = 42) and TP53-wild-type (TP53-WT) AML (n = 22) and 45 BM samples from patients who received flotetuzumab for relapsed/refractory (R/R) AML (15 cases with TP53 mutations and/or 17p deletion). The comparison between TP53-mutated and TP53-WT primary BM samples showed higher expression of IFNG, FOXP3, immune checkpoints, markers of immune senescence, and phosphatidylinositol 3-kinase-Akt and NF-κB signaling intermediates in the former cohort and allowed the discovery of a 34-gene immune classifier prognostic for survival in independent validation series. Finally, 7 out of 15 patients (47%) with R/R AML and TP53 abnormalities showed complete responses to flotetuzumab (<5% BM blasts) on the CP-MGD006-01 clinical trial (NCT #02152956) and had significantly higher tumor inflammation signature, FOXP3, CD8, inflammatory chemokine, and PD1 gene expression scores at baseline compared with nonresponders. Patients with TP53 abnormalities who achieved a complete response experienced prolonged survival (median, 10.3 months; range, 3.3-21.3 months). These results encourage further study of flotetuzumab immunotherapy in patients with TP53-mutated AML.

Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.

Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To find susceptibility genes and develop a novel predictive model of ulcerative colitis, two sets of cases and a control group containing the ulcerative colitis gene expression profile (training set GSE109142 and validation set GSE92415) were downloaded and used to identify differentially expressed genes. A total of 781 upregulated and 127 downregulated differentially expressed genes were identified in GSE109142. The random forest algorithm was introduced to determine 1 downregulated and 29 upregulated differentially expressed genes contributing highest to ulcerative colitis occurrence. Expression data of these 30 genes were transformed into gene expression scores, and an artificial neural network model was developed to calculate differentially expressed genes weights to ulcerative colitis. We established a universal molecular prognostic score (mPS) based on the expression data of the 30 genes and verified the mPS system with GSE92415. Prediction results agreed with that of an independent data set (ROC-AUC=0.9506/PR-AUC=0.9747). Our research creates a reliable predictive model for the diagnosis of ulcerative colitis, and provides an alternative marker panel for further research in disease early screening

Abstract 4397: Pathway-based drug combinatory synergy prediction using gene expression and essentiality data

Abstract Background: Experiment based drug combinatory synergy discovery is limited in a moderate scale. Systems biology models can substantially widen the search space, and discover novel mechanisms. While most of systems pharmacology models were designed to optimize the predictive performance for the drug combination synergy, they were limited by their lack of mechanistic interpretations. The gene essentiality data generated from RNAi screening have not been integrated into the systems pharmacology model yet. Methods: Drug combinatory synergy data from NCI-ALMANAC was used in this research. Cancer cell line gene expression and essential score (RNAi screening from DepMap portal), drug targets and KEGG pathways were used in our systems pharmacology model. Two types of models were constructed. The first model predicts a drug combination's synergy using various pathways among various cell lines. The second model predicts various drug combinatory synergy in a cell line. Machine learning approaches, such as SVR, Ridge regression, Random forest and Logistic regulation were investigated in developing this model. Our predictive models were built upon 43 cell lines with both baseline gene expression and essential scores, 165 KEGG pathways, and 198 drug pairs who have at least synergistic drug combinatory effects in 3 or more cell lines. Results: In predicting drug combinatory synergy from both predictive models, the mean R square was merely 0.006 using individual gene expression or essentiality data. The mean R-square increased to 0.022 when using pathways. In drug combination specific predictive model (model 1), 64 and 62 drug combinations were related to more than 10 pathways which had enriched essential and expression genes, respectively. The correlation between expression enrich pathways and essential enriched pathways is only 0.04. In the cell line specific predictive model (model 2), drug combination synergy score from 14 cell lines can be predicted with more than 150 pathways, and 5 cell lines can be predicted with less than 10 pathways. Conclusion: Pathway-based models are more powerful than gene level-based models in predicting drug combination synergy. Gene expressions and essential genes provide much different information in predicting drug combination synergy. Drug combination synergy prediction and its related pathways are dramatically different among different cancer cell lines. Citation Format: Jin Li, Xue Wu, Yang Huo, Enze Liu, Zhi Zeng, Lijun Cheng, Lang Li. Pathway-based drug combinatory synergy prediction using gene expression and essentiality data [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4397.

Abstract 3412: 36-months and 18-months relapse-free survival after (neo)adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma patients - update of the OpACIN and OpACIN-neo trials

Abstract Introduction The outcome of high-risk stage III melanoma patients was poor with a 5-year overall survival (OS) rate of &amp;lt;50%. Adjuvant ipilimumab (IPI) improved the relapse-free survival (RFS) and OS, and adjuvant anti-PD-1 improved the RFS further. Preclinical data suggested that neoadjuvant therapy may be more effective than adjuvant therapy due to broader immune activation. The OpACIN trial compared neoadjuvant IPI plus nivolumab (NIVO) versus adjuvant IPI plus NIVO, while the subsequent OpACIN-neo trial tested three different dosing schedules of neoadjuvant IPI plus NIVO only. Neoadjuvant IPI plus NIVO induced high pathologic response rates of 74-78%. Here, we present the 36- and 18-months RFS update of the OpACIN and OpACIN-neo trial, respectively. Methods The phase 1b OpACIN trial randomized 20 stage IIIB/IIIC melanoma patients to receive either 4 cycles of adjuvant IPI 3 mg/kg plus NIVO 1 mg/kg or 2 cycles of neoadjuvant IPI plus NIVO at the same dose followed by 2 cycles adjuvant IPI plus NIVO. In the OpACIN-neo trial, 86 patients were randomized to 2 cycles neoadjuvant in arm A: 2x IPI 3 mg/kg plus NIVO 1 mg/kg q3w (n=30), arm B: 2x IPI 1 mg/kg plus NIVO 3 mg/kg q3w (n=30), and arm C: 2x IPI 3 mg/kg q3w followed immediately by 2x NIVO 3 mg/kg q3w (n=26). Pathologic response was defined as &amp;lt;50% viable tumor cells and centrally reviewed by a blinded pathologist. RFS rates were estimated using the Kaplan-Meier method. Results After a median follow-up of 36 months for the OpACIN and 18 months for the OpACIN-neo trial, only 1 of 71 patients (1.4%) with a pathologic response on neoadjuvant therapy had relapsed, versus 15 of 23 patients (65.2%) without a pathologic response. The estimated 3-year RFS rate for the neoadjuvant arm was 80% (95% CI: 59%-100%) versus 60% (95% CI: 36%-100%) for the adjuvant arm in the OpACIN trial. The median RFS was not reached in any of the arms within the OpACIN-neo trial. Estimated 18-months RFS rate was 85% (95% CI: 78%-93%) for all patients; for arm A 90% (95% CI: 80%-100%), for arm B 82% (95% CI: 70%-98%) and for arm C 83% (95% CI: 70%-100%). Translational analyses showed that tumor mutational burden and interferon-γ gene expression score at baseline, both separate and combined, can function as predictors of response. Conclusions OpACIN showed for the first time a potential benefit of neoadjuvant versus adjuvant immunotherapy, while OpACIN-neo confirmed the high pathologic response rates which can be achieved by neoadjuvant IPI plus NIVO. Both trials argue for pathologic response as a surrogate markers for RFS. Clinical trial information: NCT02437279, NCT02977052 Citation Format: Christian U. Blank, Judith M. Versluis, Elisa A. Rozeman, Alexander M. Menzies, Irene L. Reijers, Oscar Krijgsman, Esmée P. Hoefsmit, Bart A. van de Wiel, Karolina Sikorska, Carolien Bierman, Petros Dimitriadis, Maria Gonzalez, Annegien Broeks, Ron M. Kerkhoven, Andrew J. Spillane, John B. Haanen, Winan J. van Houdt, Robyn P. Saw, Hanna Eriksson, Alexander C. van Akkooi, Richard A. Scolyer, Ton N. Schumacher, Georgina V. Long. 36-months and 18-months relapse-free survival after (neo)adjuvant ipilimumab plus nivolumab in macroscopic stage III melanoma patients - update of the OpACIN and OpACIN-neo trials [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3412.

Neuroendocrine differentiation in usual-type prostatic adenocarcinoma: Molecular characterization and clinical significance.

Small cell neuroendocrine (NE) carcinomas of the prostate classically lose androgen receptor (AR) expression, may harbor loss of the RB1, TP53, and PTEN tumor suppressor genes, and are associated with a poor prognosis. However usual-type adenocarcinomas may also contain areas of NE differentiation, and in this context the molecular features and biological significance are less certain. We examined the molecular phenotype and oncologic outcomes of primary prostate adenocarcinomas with ≥5% NE differentiation (≥5% chromogranin A-positive NE cells in any given tumor spot on tissue microarray) using threeindependent study sets: a set of tumors with paneth cell-like NE differentiation (n = 26), a retrospective case-cohort of intermediate- and high-risk patients enriched for adverse outcomes (n = 267), and primary tumors from a retrospective series of men with eventual castration-resistant metastatic prostate cancer (CRPC) treated with abiraterone or enzalutamide (n = 55). Benign NE cells expressed significantly lower quantified AR levels compared withpaired benign luminal cells (P < .001). Similarly, paneth-like NE carcinoma cells or carcinoma cells expressing chromogranin A expressed significantly lower quantified AR levels than paired non-NE carcinoma cells (P < .001). Quantified ERG protein expression, was also lower in chromogranin A-labeled adenocarcinoma cells compared withunlabeled cells (P < .001) and tumors with NE differentiation showed lower gene expression scores for AR activity compared withthose without. Despite evidence of lower AR signaling, adenocarcinomas with NE differentiation did not differ by prevalence of TP53 missense mutations, or PTEN or RB1 loss, compared withthose without NE differentiation. Finally, NE differentiation was not associated with time to metastasis in intermediate- and high-risk patients (P = .6 on multivariate analysis), nor with progression-free survival in patients with CRPC treated with abiraterone or enzalutamide (P = .9). NE differentiation in usual-type primary prostate adenocarcinoma is a molecularly and clinically distinct form of lineage plasticity from that occurring in small cell NE carcinoma.

Abstract IA12: The Ovarian Tumour Tissue Analysis Consortium: Stratified Prognosis of Ovarian Tumors (OTTA-SPOT) signature for high-grade serous ovarian cancer

Abstract Background: High-grade serous ovarian cancer (HGSOC) is the most common and aggressive epithelial ovarian cancer. HGSOC has poor survival, with five-year survival of less than 40%, as it is often diagnosed at a late stage. The median overall survival (OS) is approximately four years. Prognostic gene expression signatures for HGSOC have been inconsistent and have not been translated into clinical practice. The aim of this study was to develop a robust prognostic signature for HGSOC, in order to identify high-risk patients requiring alternative treatments. Methods: A meta-analysis of 1,455 tumors was performed and 200 prognostic genes were selected for expression profiling. An additional 315 candidate genes were selected from the literature, drug-targetable pathways, and other hypotheses. NanoString expression analysis of the 513 genes was performed on formalin-fixed, paraffin-embedded (FFPE) tumor tissue from 3,769 women with HGSOC from the Ovarian Tumor Tissue Analysis (OTTA) Consortium. A prognostic model for 5-year survival was developed using regression-based and machine learning methods. The model was trained on 2,702 tumors and evaluated on an independent set of 1,067 tumors. A NanoString expression analysis was performed on 2,692 additional tumors, for a subset of 218 of the genes, including the prognostic signature. Results: Expression of 276 genes was associated with OS (false discovery rate (FDR) &amp;lt; 0.05) in single-gene analyses adjusted for age, stage, and race. The top five genes were TAP1, ZFHX4, CXCL9, FBN1, and PTGER3 (p &amp;lt;&amp;lt; 0.001). A 101-gene prognostic signature was established, where a gain of one standard deviation in the gene expression score conferred a greater than two-fold increase in risk of death (HR (hazard ratio) = 2.35 [2.02, 2.71]; p &amp;lt;&amp;lt; 0.001). Median survival by quintile group was 9.5, 5.4, 3.8, 3.2, and 2.3 years. Sensitivity analyses, applying the signature to specific patient groups, showed that the prognostic power of the signature is not explained by residual disease, treatment, BRCA status, or CD8 score. The prognostic signature was enriched in pathways with treatment implications, such as PI3K, GPCR, and immune. This signature is suitable for use in FFPE tumor material and future cases can be assigned an HR from the gene expression score. The signature was developed in cases that did not receive neoadjuvant treatment (NACT); however, application to NACT cases was assessed in the second NanoString expression analysis. Conclusion: The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium – Stratified Prognosis of Ovarian Tumors) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. Citation Format: Joshua Millstein, Timothy Budden, Ellen L. Goode, Michael S. Anglesio, Aline Talhouk, OTTA consortium, David G. Huntsman, David D. Bowtell, James D. Brenton, Jennifer A. Doherty, Paul P.D. Pharoah, Susan J. Ramus. The Ovarian Tumour Tissue Analysis Consortium: Stratified Prognosis of Ovarian Tumors (OTTA-SPOT) signature for high-grade serous ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr IA12.

A blood RNA transcript signature for TB exposure in household contacts

BackgroundCurrent tools for diagnosing latent TB infection (LTBI) detect immunological memory of past exposure but are unable to determine whether exposure is recent. We sought to identify a whole-blood transcriptome signature of recent TB exposure.MethodsWe studied household contacts of TB patients; healthy volunteers without recent history of TB exposure; and patients with active TB. We performed whole-blood RNA sequencing (in all), an interferon gamma release assay (IGRA; in contacts and healthy controls) and PET/MRI lung scans (in contacts only). We evaluated differentially-expressed genes in household contacts (log2 fold change ≥1 versus healthy controls; false-discovery rate < 0.05); compared these to differentially-expressed genes seen in the active TB group; and assessed the association of a composite gene expression score to independent exposure/treatment/immunological variables.ResultsThere were 186 differentially-expressed genes in household contacts (n = 26, age 22–66, 46% male) compared with healthy controls (n = 5, age 29–38, 100% male). Of these genes, 141 (76%) were also differentially expressed in active TB (n = 14, age 27–69, 71% male). The exposure signature included genes from inflammatory response, type I interferon signalling and neutrophil-mediated immunity pathways; and genes such as BATF2 and SCARF1 known to be associated with incipient TB. The composite gene-expression score was higher in IGRA-positive contacts (P = 0.04) but not related to time from exposure, isoniazid prophylaxis, or abnormalities on PET/MRI (all P > 0.19).ConclusionsTranscriptomics can detect TB exposure and, with further development, may be an approach of value for epidemiological research and targeting public health interventions.

Prediagnostic 25-Hydroxyvitamin D Concentrations in Relation to Tumor Molecular Alterations and Risk of Breast Cancer Recurrence.

Although vitamin D inhibits breast tumor growth in experimental settings, the findings from population-based studies remain inconclusive. Our goals were to investigate the association between prediagnostic plasma 25-hydroxyvitamin D [25(OH)D] concentration and breast cancer recurrence in prospective epidemiologic studies and to explore the molecular underpinnings linking 25(OH)D to slower progression of breast cancer in the Nurses' Health Studies (NHS, N = 659). Plasma 25(OH)D was measured with a high-affinity protein-binding assay and a radioimmunoassay. We profiled transcriptome-wide gene expression in breast tumors using microarrays. Hazard ratios (HR) of breast cancer recurrence were estimated from covariate-adjusted Cox regressions. We examined differential gene expression in association with 25(OH)D and employed pathway analysis. We derived a gene expression score for 25(OH)D, and assessed associations between the score and cancer recurrence. Although 25(OH)D was not associated with breast cancer recurrence overall [HR = 0.97; 95% confidence interval (CI), 0.88-1.08], the association varied by estrogen-receptor (ER) status (P interaction = 0.005). Importantly, among ER-positive stage I to III cancers, every 5 ng/mL increase in 25(OH)D was associated with a 13% lower risk of recurrence (HR = 0.87; 95% CI, 0.76-0.99). A null association was observed for ER-negative cancers (HR = 1.07; 95% CI, 0.91-1.27). Pathway analysis identified multiple gene sets that were significantly (FDR < 5%) downregulated in ER-positive tumors of women with high 25(OH)D (≥30 ng/mL), compared with those with low levels (<30 ng/mL). These gene sets are primarily involved in tumor proliferation, migration, and inflammation. 25(OH)D score derived from these gene sets was marginally associated with reduced risk of recurrence in ER-positive diseases (HR = 0.77; 95% CI, 0.59-1.01) in the NHS studies; however no association was noted in METABRIC, suggesting that further refinement is need to improve the generalizability of the score. Our findings support an intriguing line of research for studies to better understand the mechanisms underlying the role of vitamin D in breast tumor progression, particularly for the ER-positive subtype. Vitamin D may present a personal-level secondary-prevention strategy for ER-positive breast cancer.

Prognostic gene expression signature for high-grade serous ovarian cancer

Background:Median overall survival (OS) for women with high-grade serous ovarian cancer (HGSOC) is ~4 years, yet survival varies widely between patients. There are no well-established, gene expression signatures associated with prognosis. The aim of this study was to develop a robust prognostic signature for OS in patients with HGSOC.Patients and methods:Expression of 513 genes, selected from a meta-analysis of 1455 tumours and other candidates, was measured using NanoString technology from formalin-fixed paraffin-embedded tumour tissue collected from 3769 women with HGSOC from multiple studies. Elastic net regularization for survival analysis was applied to develop a prognostic model for 5-year OS, trained on 2702 tumours from 15 studies and evaluated on an independent set of 1067 tumours from six studies.Results:Expression levels of 276 genes were associated with OS (false discovery rate < 0.05) in covariate-adjusted single-gene analyses. The top five genes were TAP1, ZFHX4, CXCL9, FBN1 and PTGER3 (P < 0.001). The best performing prognostic signature included 101 genes enriched in pathways with treatment implications. Each gain of one standard deviation in the gene expression score conferred a greater than twofold increase in risk of death [hazard ratio (HR) 2.35, 95% confidence interval (CI) 2.02–2.71; P < 0.001]. Median survival [HR (95% CI)] by gene expression score quintile was 9.5 (8.3 to –), 5.4 (4.6–7.0), 3.8 (3.3–4.6), 3.2 (2.9–3.7) and 2.3 (2.1–2.6) years.Conclusion:The OTTA-SPOT (Ovarian Tumor Tissue Analysis consortium - Stratified Prognosis of Ovarian Tumours) gene expression signature may improve risk stratification in clinical trials by identifying patients who are least likely to achieve 5-year survival. The identified novel genes associated with the outcome may also yield opportunities for the development of targeted therapeutic approaches.