Gene Expression Subsets Research Articles

Abstract P1-06-07: Enhanced differentiation of clinical behavior by breast carcinomas utilizing quantification of estrogen and progestin receptor proteins and gene expression subsets

Abstract Background: IHC analyses of clinical biomarkers for breast cancer management yield semi-quantitative results potentially complicated by variation in methods and interpretation. We are mining a comprehensive database established over four decades that contains deidentified results of quantified protein and RNA biomarkers with clinical outcomes to detect candidates for companion diagnostics and molecular targets. Assays were performed in a Reference Laboratory holding both CLIA and Commonwealth of Kentucky licenses. Methods: This retrospective investigation utilized ER/PR protein levels, expressed as fmol/mg cytosol protein, that were quantified for each of 2339 carcinoma biopsies with FDA-approved kits and cut-off values by radio-ligand binding assay (LBA, NEN/DuPont) and/or enzyme immunoassay (EIA, Abbott Labs). Of these, 454 specimens had both LBA and EIA results recorded. Biomarker results and de-identified clinical outcomes were examined using REMARK criteria. Gene expression, quantified biomarkers, features of primary breast cancers and clinical patient outcomes were analyzed by univariable and multivariable Cox regressions, Fisher’s Exact Test, Kaplan Meier plots and with R software v4.0.0. Microarray results of ~22,000 genes were obtained from RNA of LCM-procured breast carcinoma cells of 247 primary breast biopsies and expression levels of 85 cancer-associated genes were determined by RTqPCR of 278 specimens after RNA extraction and purification with established procedures. Results: Quantified levels of both ER and PR protein were expressed to a greater extent in primary carcinomas from post-menopausal patients compared to cancers from premenopausal women regardless of assay type (p = 0.005). ESR1 expression by microarray was only greater in LCM-procured carcinoma cells of post-menopausal patients while both ESR1 and PGR relative expression levels measured by qPCR were greater in tissue biopsies of post-menopausal women (p = 0.05). Box plots of untransformed EIA/LBA results of either ER (n=454) or PR (n=452) using specimens on which both quantifying assays were performed revealed a significant positive ER bias by EIA (median ratio=1.54) compared to that of PR (median ration=1.13). Transformed data of ratios confirmed this observation. Kaplan Meier plots of patient outcomes with ER or PR or both assessed by each assay type suggested LBA was a slightly better predictor. Microarray analyses of LCM-procured cells revealed 2994 genes distinguishing ER+ from ER- breast cancers of which ~200 genes were identified that differentiated 4 distinct molecular subtypes (2 ER+ and 2 ER-) exhibiting different outcomes upon Kaplan-Meier analyses. Expression levels of the 85 genes (including ERBB2), validated by qPCR with RNA from biopsy tissue sections, were evaluated relative to quantified levels of either ER or PR protein or both in primary breast cancer biopsies. Collectively, use of quantified ER/PR protein or ESR1/PGR expression with clinical outcomes enhanced identification of small molecular signatures and drug development candidates. Conclusions: Measurements of ER, PR and HER2 proteins with tests that quantify their levels as well as by microarray and qPCR assessment of ESR1, PGR and ERBB2 relative gene expression were correlated with prediction of clinical outcomes of breast carcinomas exhibiting various features (e.g., pathology classification, TNBC). Results reinforced importance of assessing levels of the clinically relevant biomarkers in a quantified fashion to enhance their use in breast cancer management and prediction of risk of recurrence. These investigations also revealed numerous over-expressed genes in carcinomas with poor clinical outcomes suggesting candidates for development of novel therapeutics. Citation Format: James L Wittliff, Michael W. Daniels. Enhanced differentiation of clinical behavior by breast carcinomas utilizing quantification of estrogen and progestin receptor proteins and gene expression subsets [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P1-06-07.

In ovo co-administration of vitamins (A and D) and probiotic lactobacilli modulates immune responses in broiler chickens

There is evidence that probiotic lactobacilli, in addition to essential vitamins, such as vitamin A and D, have immunomodulatory properties that enhance immune response of neonatal chickens against infections. The present study evaluated the effects of in ovo administration of retinoic acid (RA), 25-Hydroxyvitamin D3 (VitD), and a lactobacilli cocktail on cytokine gene expression, antibody responses and spleen cell subsets in chickens. RA (90 µmol/egg) and VitD (0.6 μg/egg) were administered in ovo, either alone or in combination with lactobacilli (107 CFU/egg), at embryonic d 18. On d 5 and 10 posthatch, gene expression and cellular composition were analyzed in the bursa of Fabricius and spleen. Birds were immunized on d 14 and 21 posthatch with 2 T-dependent antigens, sheep red blood cells (SRBC) and keyhole limpet hemocyanin (KLH), to assess their antibody responses. Sera were collected from the immunized chickens on d 14, 21, 28, and 35 posthatch. The results demonstrated that lactobacilli treatment increased the number of monocyte/macrophages (KUL01+) and CD3+CD4+ T cells in the spleen, and enhanced serum anti-KLH IgM and IgY on d 14 postprimary immunization (P < 0.05). RA significantly increased serum IgY and IgM titers to KLH and enhanced the expression of interferon (IFN)-α, interleukin (IL)-1β, IL-6, IL-8, IL-12, IL-13, and transforming growth factor-β (TGF-β) in the bursa of Fabricius (P < 0.05). The percentage of CD3+CD8+ T cells, and monocyte/macrophages (KUL01+) was elevated in the spleen as well (P < 0.05). These findings reveal that prehatch administration of RA improves immunocompetency of neonatal chickens by increasing the production of cytokines that regulate innate immunity and through enhancing antibody-mediated response against T-dependent antigens.

Diminished Efficacy of Programmed Death-(Ligand)1 Inhibition in STK11- and KEAP1-Mutant Lung Adenocarcinoma Is Affected by KRAS Mutation Status

IntroductionSTK11 and KEAP1 mutations (STK11 mutant [STK11MUT] and KEAP1MUT) are among the most often mutated genes in lung adenocarcinoma (LUAD). Although STK11MUT has been associated with resistance to programmed death-(ligand)1 (PD-[L]1) inhibition in KRASMUT LUAD, its impact on immunotherapy efficacy in KRAS wild-type (KRASWT) LUAD is currently unknown. Whether KEAP1MUT differentially affects outcomes to PD-(L)1 inhibition in KRASMUT and KRASWT LUAD is also unknown. MethodsClinicopathologic and genomic data were collected from September 2013 to September 2020 from patients with advanced LUAD at the Dana-Farber Cancer Institute/Massachusetts General Hospital cohort and the Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center cohort. Clinical outcomes to PD-(L)1 inhibition were analyzed according to KRAS, STK11, and KEAP1 mutation status in two independent cohorts. The Cancer Genome Atlas transcriptomic data were interrogated to identify differences in tumor gene expression and tumor immune cell subsets, respectively, according to KRAS/STK11 and KRAS/KEAP1 comutation status. ResultsIn the combined cohort (Dana-Farber Cancer Institute/Massachusetts General Hospital + Memorial Sloan Kettering Cancer Center/MD Anderson Cancer Center) of 1261 patients (median age = 61 y [range: 22–92], 708 women [56.1%], 1065 smokers [84.4%]), KRAS mutations were detected in 536 cases (42.5%), and deleterious STK11 and KEAP1 mutations were found in 20.6% (260 of 1261) and 19.2% (231 of 1202) of assessable cases, respectively. In each independent cohort and in the combined cohort, STK11 and KEAP1 mutations were associated with significantly worse progression-free (STK11 hazard ratio [HR] = 2.04, p < 0.0001; KEAP1 HR = 2.05, p < 0.0001) and overall (STK11 HR = 2.09, p < 0.0001; KEAP1 HR = 2.24, p < 0.0001) survival to immunotherapy uniquely among KRASMUT but not KRASWT LUADs. Gene expression ontology and immune cell enrichment analyses revealed that the presence of STK11 or KEAP1 mutations results in distinct immunophenotypes in KRASMUT, but not in KRASWT, lung cancers. ConclusionsSTK11 and KEAP1 mutations confer worse outcomes to immunotherapy among patients with KRASMUT but not among KRASWT LUAD. Tumors harboring concurrent KRAS/STK11 and KRAS/KEAP1 mutations display distinct immune profiles in terms of gene expression and immune cell infiltration.

Multi-Omics Analyses Show Disease, Diet, and Transcriptome Interactions With the Virome

The gut virome includes eukaryotic viruses and bacteriophages that can shape the gut bacterial community and elicit host responses. The virome can be implicated in diseases, such as irritable bowel syndrome (IBS), where gut bacteria play an important role in pathogenesis. We provide a comprehensive and longitudinal characterization of the virome, including DNA and RNA viruses and paired multi-omics data in a cohort of healthy subjects and patients with IBS. We selected 2 consecutive stool samples per subject from a longitudinal study cohort and performed metagenomic sequencing on DNA and RNA viruses after enriching for viral-like particles. Viral sequence abundance was evaluated over time, as well as in the context of diet, bacterial composition and function, metabolite levels, colonic gene expression, host genetics, and IBS subsets. We found that the gut virome was temporally stable and correlated with the colonic transcriptome. We identified IBS-subset-specific changes in phage populations; Microviridae, Myoviridae, and Podoviridae species were elevated in diarrhea-predominant IBS, and other Microviridae and Myoviridae species were elevated in constipation-predominant IBS compared to healthy controls. We identified correlations between subsets of the virome and bacterial composition (unclassifiable "dark matter" and phages) and diet (eukaryotic viruses). We found that the gut virome is stable over time but varies among subsets of patients with IBS. It can be affected by diet and potentially influences host function via interactions with gut bacteria and/or altering host gene expression.

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement

ObjectiveWe sought to determine histologic and gene expression features of clinical improvement in early diffuse cutaneous systemic sclerosis (dcSSc; scleroderma).MethodsFifty-eight forearm biopsies were evaluated from 26 individuals with dcSSc in...

Machine learning predicts stem cell transplant response in severe scleroderma

ObjectiveThe Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial demonstrated clinical benefit of haematopoietic stem cell transplant (HSCT) compared with cyclophosphamide (CYC). We mapped PBC (peripheral blood cell) samples from the SCOT...

Regulator combinations identify systemic sclerosis patients with more severe disease.

Systemic sclerosis (SSc) is a heterogeneous autoimmune disorder that results in skin fibrosis, autoantibody production, and internal organ dysfunction. We previously identified 4 “intrinsic” subsets of SSc based upon skin gene expression that are found across organ systems. Gene expression regulators that underlie the SSc-intrinsic subsets, or are associated with clinical covariates, have not been systematically characterized. Here, we present a computational framework to calculate the activity scores of gene expression regulators and identify their associations with SSc clinical outcomes. We found that regulator activity scores can reproduce the intrinsic molecular subsets, with distinct sets of regulators identified for inflammatory, fibroproliferative, limited, and normal-like samples. Regulators most highly correlated with modified Rodnan skin score (MRSS) also varied by intrinsic subset. We identified subgroups of patients with fibroproliferative and inflammatory SSc with more severe pathophenotypes, such as higher MRSS and increased likelihood of interstitial lung disease (ILD). Using an independent cohort, we show that the group with more severe ILD was more likely to show forced vital capacity decline over a period of 36–54 months. Our results demonstrate an association among the activation of regulators, gene expression subsets, and clinical variables that can identify patients with SSc with more severe disease.

Effect of STK11 mutations on efficacy of PD-1 inhibition in non-small cell lung cancer (NSCLC) and dependence on KRAS mutation status.

e15113 Background: STK11 mutations ( STK11m) have been associated with resistance to ICI in KRAS-mutant ( KRASm) NSCLC. Whether STK11m status also impacts clinical outcomes to ICI in KRAS wild-type (wt) NSCLC is unknown. Methods: We analyzed clinical outcomes of patients (pts) with NSCLC treated with ICI according to KRAS and STK11 mutation status in independent discovery (DFCI+MGH) and validation (MSKCC) cohorts. TCGA and xCell data were interrogated to identify differences in tumor gene expression and tumor immune cell subsets, respectively, according to KRAS/ STK11 co-mutation status. Results: Of 1195 pts with advanced nonsquamous NSCLC treated with ICI, 447 (37.4%) had a KRASm, 252 (21.1%) had pathogenic STK11 mutations, and 128 (10.7%) had concurrent KRASm and STK11m. ICI outcomes for the discovery and validation cohorts in KRASm and KRASwt cases by STK11 mutation status are shown in Table. In the combined cohort (discovery+validation), STK11m was associated with significantly worse outcomes to ICI among KRASm cases: ORR 10.2% vs 30.7%, P &lt; 0.001; median progression-free survival (mPFS): 2.0 vs 4.8 months (mo), HR:0.49 [95%CI:0.39-0.61], P &lt; 0.0001; median overall survival (mOS): 6.1 vs 16.9 mo, HR:0.50 [95%CI:0.39-0.63], P &lt; 0.0001. In multivariable analysis, STK11m was associated with significantly shorter PFS (HR:0.56, P = 0.002) and OS (HR:0.57, P = 0.006). By contrast, STK11m had no impact on ICI outcomes among KRASwt cases: ORR 24.2% vs 19.2%, P = 0.21; mPFS: 2.5 vs 2.8 mo, HR:0.98 [95%CI:0.79-1.21], P = 0.89; mOS: 12.0 vs 11.5 mo, HR:1.06 [95%CI:0.85-1.33], P = 0.57. Among KRASwt cases, STK11m had no impact on ICI outcomes among both smokers and never smokers, when analyzed separately. Gene ontology analysis from TCGA revealed that among KRASm but not KRASwt NSCLC, STK11m was associated with the downregulation of MHC class II-related genes (P = 0.02). Cell subset transcriptome analysis showed significantly lower proportions of M1 macrophages among KRASm/ STK11m but not among KRASwt/ STK11m NSCLCs (P &lt; 0.01). Conclusions: STK11m are associated with resistance to ICI in KRASm but not KRASwt NSCLC. STK11m/ KRASm vs STK11m/ KRASwt NSCLC have distinct immunophenotypes. [Table: see text]

Abstract P1-09-03: Clinically relevant gene expression subsets deciphered from breast carcinomas classified by quantified expression levels of estrogen and progestin receptors

Abstract Background: Prior to standardization of IHC parameters by CAP/ASCO Guidelines in 2010 (Hammond et al., Arch Pathol Lab Med), ER/PR measurements were highly variable (e.g., fixation/staining, observer scoring). While serving as the National Reference Laboratory for NCI supported clinical trials by the NSABP, SWOG, CALGB, NCCTG, ECOG and SECSG, both EIA and radio-ligand binding assays (LBA) were employed that quantified ER/PR content and activities. Using ER/PR levels, we assessed relationships of qPCR expression of 85 candidate genes from 569 primary cancers with clinical outcomes to decipher molecular signatures that predict risk of recurrence. Methods: This retrospective study used a unique dataset of de-identified ER/PR results of 1220 primary cancers from patients with clinical follow-up, stored in an IRB-approved Database. ER/PR protein levels, expressed as fmol/mg cytosol protein, were quantified earlier from each carcinoma with FDA-approved kits using either enzyme immunoassay (n = 751, Abbott Labs) or LBA (n = 552, NEN/DuPont). Relationships between ER/PR content assessed by LBA compared to that from EIA were examined. Results obtained from 1988-1996 and de-identified clinical outcomes were examined using REMARK criteria in a CLIA licensed laboratory. Gene expression, ER/PR quantified by LBA or EIA, features of primary breast cancers and clinical outcomes were analyzed by univariable and multivariable Cox regressions, Kaplan Meier plots and LASSO with R software v3.6.0. Gene expression levels were validated by qPCR while molecular signatures were externally validated with SurvExpress. (Aguirre-Gamboa et al. PLoS One e742502013). Results: Examination of patient survival by Kaplan-Meier analyses using cancers classified by quantified ER or PR (regardless of by EIA or by LBA) revealed RFS and OS were related to increased content. Relationships RFS/OS with Kd values from LBA were examined. Also, differences in ER/PR status of carcinomas were associated with RFS and OS of patients (i.e., ER+/PR+ was related to increased RFS and OS while ER-/PR- status was associated with reduced RFS and OS). Univariable Cox regression of expression of each of the 85 genes identified 18 that predicted RFS while 22 genes predicted OS, confirmed by Kaplan-Meier Analyses. Multiple imputation by chained equations (‘MICE’, Zhang, Ann Transl Med. 2016) imputed missing qPCR values in order to utilize all 569 patients and 85 genes. With the ‘SGL’ package in R, an optimal L2 penalty determined the best fit LASSO model (algorithm sets minimum size for each beta coefficient and its associated gene to be included in the final Cox survival models). Sixteen gene subsets were deciphered according to quantified ER, PR or ER/PR status predicted either RFS or OS or both reflecting the increased or decreased hazard for a one unit change in a gene while controlling for other gene associations. Conclusion: Expression of each gene in each of the 16 subsets exhibits a hazard ratio, when taken jointly, predicts either PFS or OS. Multidimensional portrayal of variation in the outcome PFS or OS is controlled by gene expression in the signature for an overall effect. Using expression results validated by qPCR, subsets of ER and/or PR related genes in primary lesions were identified that predict a patient's risk of recurrence and overall survival. Collectively, results suggest that gene expression profiles based on quantified ER/PR content of a biopsy serve as value-added biomarkers for assessing prognosis of breast carcinomas and identifying candidates for developing companion diagnostics. Supported in part by grants to JLW from Phi Beta Psi Sorority Charity Trust, University of Louisville, Office of the EVPR, and a CTSP award, Commonwealth of Kentucky. WAS is the recipient of a fellowship from Bates College, ME. Citation Format: James L Wittliff, William A. Stern, Zohair R. Hameed, Michael W. Daniels. Clinically relevant gene expression subsets deciphered from breast carcinomas classified by quantified expression levels of estrogen and progestin receptors [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-09-03.

Dynamic changes in human HLA-DRA gene expression and Th cell subsets in sepsis: Indications of immunosuppression and associated outcomes.

Sepsis is a life-threatening disease that is an immune disorder response that causes multiple organ dysfunction. In this study, we investigated the dynamic changes in mRNA expression of HLA-DRA gene and the specific transcription factor of helper T cell subsets to explore long-term immunophenotyping and its relationship with prognosis. Seventy-eight sepsis patients and twelve healthy controls were recruited in this study. Blood samples were collected at eight-time points during their septic course and were assayed for the gene expression of HLA-DRA and T helper cell subset-specific transcription factors (T-bet: Th1, GATA3: Th2, Foxp3: Treg, RORC: Th17). The levels of HLA-DRA in survivors gradually increased but were maintained at lower levels in non-survivors. The specific transcription factor of Th1 and Th2 cells, T-bet and GATA-3 were significantly lower in sepsis patients than in normal controls, and the non-survivors showed significantly lower levels than the survivors (P<.05). RORC and FOXP3, the specific transcription factor of Treg and Th17 were significantly higher in survivors than in non-survivors and normal controls (P<.05). T-bet and GATA-3 had a linear correlation with HLA-DRA expression (P<.01). The dynamic changes in HLA-DRA expression in peripheral blood could accurately reflect the immune status of sepsis patients, and the reduction in HLA-DRA may be an important reason for abnormal T cell differentiation. The sustained low levels of the Th cell subsets (Th1 and Th2) suggest the suppression of adaptive immunity, and this persistent immunosuppression may be the leading cause of death in septic patients.

A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets.

High-throughput gene expression profiling of tissue samples from patients with systemic sclerosis (SSc) has identified 4 "intrinsic" gene expression subsets: inflammatory, fibroproliferative, normal-like, and limited. Prior methods required agglomerative clustering of many samples. In order to classify individual patients in clinical trials or for diagnostic purposes, supervised methods that can assign single samples to molecular subsets are required. We undertook this study to introduce a novel machine learning classifier as a robust accurate intrinsic subset predictor. Three independent gene expression cohorts were curated and merged to create a data set covering 297 skin biopsy samples from 102 unique patients and controls, which was used to train a machine learning algorithm. We performed external validation using 3 independent SSc cohorts, including a gene expression data set generated by an independent laboratory on a different microarray platform. In total, 413 skin biopsy samples from 213 individuals were analyzed in the training and testing cohorts. Repeated cross-fold validation identified consistent and discriminative markers using multinomial elastic net, performing with an average classification accuracy of 87.1% with high sensitivity and specificity. In external validation, the classifier achieved an average accuracy of 85.4%. Reanalyzing data from a previous study, we identified subsets of patients that represent the canonical inflammatory, fibroproliferative, and normal-like subsets. We developed a highly accurate classifier for SSc molecular subsets for individual patient samples. The method can be used in SSc clinical trials to identify an intrinsic subset on individual samples. Our method provides a robust data-driven approach to aid clinical decision-making and interpretation of heterogeneous molecular information in SSc patients.

Research in Brief.

A once-weekly dose of abatacept (CTLA-4-Ig) is well tolerated but does not improve skin disease in diffuse cutaneous systemic sclerosis (dcSSc), a recent phase 2 trial suggests. Dinesh Khanna and colleagues randomly assigned patients with dcSSc to receive subcutaneous abatacept (n=44) or placebo (n=44). At 12 months, there was no difference in the change in modified Rodnan skin score (mRSS; primary outcome) between the two groups (difference −1·75; 95% CI −4·93–1·43; p=0·28). In the abatacept group, fewer patients required escape therapy for worsening disease (16% vs 36%), and fewer experienced adverse events (82% vs 91%) compared to placebo treated patients. Patient-reported outcomes were also significantly better in the abatacept group. When patients were divided into subgroups based on baseline skin gene expression profiles, the decline in mRSS over 12 months was significantly improved by abatacept over placebo for patients in the inflammatory and normal-like subgroups, but not in patients in the fibroproliferative subgroup, suggesting that intrinsic skin gene expression subsets might predict differential response to abatacept.

Abstract P1-01-12: Expression of autophagy related genes impacts clinical outcomes of human breast carcinoma and is associated with estrogen and progestin receptor status

Abstract The dual role of autophagy in breast cancer initiation, progression and responsiveness to various therapies is the focus of extensive studies. Our goal is to assess the relationship of expression of certain autophagy related genes in primary breast carcinomas to predict risk of recurrence. Our hypothesis includes the caveat that unique gene expression subsets will be deciphered by utilizing Laser Capture Microdissected breast carcinoma cells from tissue biopsies containing many cell types. Methods: Comprehensive analyses of de-identified biomarker results, characteristics of 247 breast carcinoma specimens and clinical outcomes were performed by univariable Cox regressions, Kaplan Meier plots and LASSO with R software version 3.2.5. Microarray analyses were performed on RNA isolated from LCM-procured carcinoma cells to identify gene signatures associated with breast cancer behavior. Results: Expression levels of 22 autophagy related genes analyzed by univariable Cox regression revealed that RB1CC1, KEAP1, ATG7, RUBCN, NOD2, HMOX1, BECN1, PIK3R4 were significant for predicting Progression Free Survival (PFS) at the discovery level of the adjusted p-value &amp;lt; 0.3. Of these, RB1CC1, KEAP1, &amp; ATG7 were significant for Overall Survival (OS) without regard to ER/PR status. Using Kaplan Meier analyses, expression levels of each of 10 candidate genes predicted PFS of which expression of 6 of these genes also predicted OS using a median split cutoff without regard to ER/PR status. Applying LASSO computations without regard to ER/PR status of the primary breast cancer, a clinically relevant gene expression profile consisting of ATG7, BCL2, HMOX1, KEAP1, NOD2, PTEN, RB1CC1, and ULK4 predicted PFS. Collectively, expression of these 8 genes with TP53 and RUBCN predicted OS without regard to ER/PR status. Violin plots of relative gene expression of each of the 22 candidate genes known to be associated with autophagy pathways revealed that ATG7, ATG12, BCL2 and BECN1 were elevated in ER+ lesions while BCL2 and BECN1 were also elevated in PR+ breast carcinomas. Expression levels of 16 of the 22 autophagy related genes examined by univariable Cox regression were related to either ER or PR status of the primary lesion and predicted either PFS or OS. Refinement of clinically relevant gene subsets was accomplished by LASSO calculations in which either the ER or PR protein status of the primary breast carcinoma was considered. Of the genes in the molecular signatures derived, expression levels in breast carcinomas separated by either ER or PR status of the lesion were tested by Kaplan Meier analyses to assess relationships to PFS and OS. Conclusions: Using gene expression results derived from microarray analyses of LCM-procured breast carcinoma cells of primary lesions, subsets of autophagy related genes were identified that predict a patient's risk of recurrence and overall survival. Expression of a number of candidate genes appears to be related to either/both the ER or PR protein status of the primary lesion. Collectively, results suggest that expression of certain autophagy related genes may serve as biomarkers for assessing prognosis of breast carcinoma thus impacting clinical management of breast cancer. Citation Format: Wittliff JL, Hameed ZR, Daniels MW, Cheng A. Expression of autophagy related genes impacts clinical outcomes of human breast carcinoma and is associated with estrogen and progestin receptor status [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-01-12.

Validation Study of an Operational Tolerance Signature in Korean Kidney Transplant Recipients.

Operational tolerance (OT), defined as maintaining stable graft function without immunosuppression after transplant surgery, is an ideal goal for kidney transplant recipients (KTRs). Recent investigations have demonstrated the distinctive features of B cells, T cells, and dendritic cell-related gene signatures and the distributions of circulating lymphocytes in these patients; nonetheless, substantial heterogeneities exist across studies. This study was conducted to determine whether previously reported candidate gene biomarkers and the profiles of lymphocyte subsets of OT could be applied in Korean KTRs. Peripheral blood samples were collected from 153 patients, including 7 operationally tolerant patients. Quantitative real-time PCR and flow cytometry were performed to evaluate gene expression and lymphocyte subsets, respectively. Patients with OT showed significantly higher levels of B cell-related gene signatures (IGKV1D-13 and IGKV4-1), while T cell-related genes (TOAG-1) and dendritic cell-related genes (BNC2, KLF6, and CYP1B1) were not differentially expressed across groups. Lymphocyte subset analyses also revealed a higher proportion of immature B cells in this group. In contrast, the distributions of CD4+ T cells, CD8+ T cells, mature B cells, and memory B cells showed no differences across diagnostic groups. An OT signature, generated by the integration of IGKV1D-13, IGKV4-1, and immature B cells, effectively discriminated patients with OT from those in other diagnostic groups. Finally, the OT signature was observed among 5.6% of patients who had stable graft function for more than 10 years while on immunosuppression. In conclusion, we validated an association of B cells and their related signature with OT in Korean KTRs.

Molecular stratification and precision medicine in systemic sclerosis from genomic and proteomic data.

The goal of this review is to summarize recent advances into the pathogenesis and treatment of systemic sclerosis (SSc) from genomic and proteomic studies. Intrinsic gene expression-driven molecular subtypes of SSc are reproducible across three independent datasets. These subsets are a consistent feature of SSc and are found in multiple end-target tissues, such as skin and esophagus. Intrinsic subsets as well as baseline levels of molecular target pathways are potentially predictive of clinical response to specific therapeutics, based on three recent clinical trials. A gene expression-based biomarker of modified Rodnan skin score, a measure of SSc skin severity, can be used as a surrogate outcome metric and has been validated in a recent trial. Proteome analyses have identified novel biomarkers of SSc that correlate with SSc clinical phenotypes. Integrating intrinsic gene expression subset data, baseline molecular pathway information, and serum biomarkers along with surrogate measures of modified Rodnan skin score provides molecular context in SSc clinical trials. With validation, these approaches could be used to match patients with the therapies from which they are most likely to benefit and thus increase the likelihood of clinical improvement.

Gene expression profiling offers insights into the role of innate immune signaling in SSc.

Systemic sclerosis (SSc) is characterized by inflammation, vascular dysfunction, and ultimately fibrosis. Progress in understanding disease pathogenesis and developing effective disease treatments has been hampered by an incomplete understanding of SSc heterogeneity. To clarify this, we have used genomic approaches to identify distinct patient subsets based on gene expression patterns in SSc skin and other end-target organs. Here, we review what is known about the gene expression-based subsets in SSc, currently defined as the inflammatory, fibroproliferative, limited, and normal-like subsets. The inflammatory subset of patients is characterized by infiltrating immune cells that include T cells, macrophages, and possibly dendritic cells, although little is known about the mediators these cells secrete and the pathways that govern cell activation. Prior studies have suggested a role for pathogens as a trigger of immune responses in SSc, and recent data have identified viral and mycobiome components as potential environmental triggers. We present a model based on analyses of gene expression data and a review of the literature, which suggests that the gene expression subsets observed in patients possibly represent distinct, interconnected molecular states of disease, to which an innate immune response is central that results in the generation of clinical disease.

Molecular characterization of systemic sclerosis esophageal pathology identifies inflammatory and proliferative signatures.

IntroductionEsophageal involvement in patients with systemic sclerosis (SSc) is common, but tissue-specific pathological mechanisms are poorly understood. There are no animal scleroderma esophagus models and esophageal smooth muscle cells dedifferentiate in culture prohibiting in vitro studies. Esophageal fibrosis is thought to disrupt smooth muscle function and lead to esophageal dilatation, but autopsy studies demonstrate esophageal smooth muscle atrophy and the absence of fibrosis in the majority of SSc cases. Herein, we perform a detailed characterization of SSc esophageal histopathology and molecular signatures at the level of gene expression.MethodsEsophageal biopsies were prospectively obtained during esophagogastroduodenoscopy in 16 consecutive SSc patients and 7 subjects without SSc. Upper and lower esophageal biopsies were evaluated for histopathology and gene expression.ResultsIndividual patient’s upper and lower esophageal biopsies showed nearly identical patterns of gene expression. Similar to skin, inflammatory and proliferative gene expression signatures were identified suggesting that molecular subsets are a universal feature of SSc end-target organ pathology. The inflammatory signature was present in biopsies without high numbers of infiltrating lymphocytes. Molecular classification of esophageal biopsies was independent of SSc skin subtype, serum autoantibodies and esophagitis.ConclusionsProliferative and inflammatory molecular gene expression subsets in tissues from patients with SSc may be a conserved, reproducible component of SSc pathogenesis. The inflammatory signature is observed in biopsies that lack large inflammatory infiltrates suggesting that immune activation is a major driver of SSc esophageal pathogenesis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0695-1) contains supplementary material, which is available to authorized users.

Gene expression changes reflect clinical response in a placebo-controlled randomized trial of abatacept in patients with diffuse cutaneous systemic sclerosis.

IntroductionSystemic sclerosis is an autoimmune disease characterized by inflammation and fibrosis of the skin and internal organs. We sought to assess the clinical and molecular effects associated with response to intravenous abatacept in patients with diffuse cutaneous systemic.MethodsAdult diffuse cutaneous systemic sclerosis patients were randomized in a 2:1 double-blinded fashion to receive abatacept or placebo over 24 weeks. Primary outcomes were safety and the change in modified Rodnan Skin Score (mRSS) at week 24 compared with baseline. Improvers were defined as patients with a decrease in mRSS of ≥30 % post-treatment compared to baseline. Skin biopsies were obtained for differential gene expression and pathway enrichment analyses and intrinsic gene expression subset assignment.ResultsTen subjects were randomized to abatacept (n = 7) or placebo (n = 3). Disease duration from first non-Raynaud’s symptom was significantly longer (8.8 ± 3.8 years vs. 2.4 ± 1.6 years, p = 0.004) and median mRSS was higher (30 vs. 22, p = 0.05) in the placebo compared to abatacept group. Adverse events were similar in the two groups. Five out of seven patients (71 %) randomized to abatacept and one out of three patients (33 %) randomized to placebo experienced ≥30 % improvement in skin score. Subjects receiving abatacept showed a trend toward improvement in mRSS at week 24 (−8.6 ± 7.5, p = 0.0625) while those in the placebo group did not (−2.3 ± 15, p = 0.75). After adjusting for disease duration, mRSS significantly improved in the abatacept compared with the placebo group (abatacept vs. placebo mRSS decrease estimate −9.8, 95 % confidence interval −16.7 to −3.0, p = 0.0114). In the abatacept group, the patients in the inflammatory intrinsic subset showed a trend toward greater improvement in skin score at 24 weeks compared with the patients in the normal-like intrinsic subset (−13.5 ± 3.1 vs. −4.5 ± 6.4, p = 0.067). Abatacept resulted in decreased CD28 co-stimulatory gene expression in improvers consistent with its mechanism of action. Improvers mapped to the inflammatory intrinsic subset and showed decreased gene expression in inflammatory pathways, while non-improver and placebos showed stable or reverse gene expression over 24 weeks.ConclusionsClinical improvement following abatacept therapy was associated with modulation of inflammatory pathways in skin.Trial registrationClinicalTrials.gov NCT00442611. Registered 1 March 2007.Electronic supplementary materialThe online version of this article (doi:10.1186/s13075-015-0669-3) contains supplementary material, which is available to authorized users.

Systems level analysis of systemic sclerosis shows a network of immune and profibrotic pathways connected with genetic polymorphisms.

Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.

Immune regulation by low doses of the DNA methyltransferase inhibitor 5-azacitidine in common human epithelial cancers

Epigenetic therapy is emerging as a potential therapy for solid tumors. To investigate its mechanism of action, we performed integrative expression and methylation analysis of 63 cancer cell lines (breast, colorectal, and ovarian) after treatment with the DNA methyltransferase inhibitor 5-azacitidine (AZA). Gene Set Enrichment Analysis demonstrated significant enrichment for immunomodulatory pathways in all three cancers (14.4-31.3%) including interferon signaling, antigen processing and presentation, and cytokines/chemokines. Strong upregulation of cancer testis antigens was also observed. An AZA IMmune gene set (AIMs) derived from the union of these immunomodulatory pathway genes classified primary tumors from all three types, into "high" and "low" AIM gene expression subsets in tumor expression data from both TCGA and GEO. Samples from selected patient biopsies showed upregulation of AIM genes after treatment with epigenetic therapy. These results point to a broad immune stimulatory role for DNA demethylating drugs in multiple cancers.