Identification of Proteome-Based Immune Subtypes of Early Hepatocellular Carcinoma and Analysis of Potential Metabolic Drivers.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, ranking fourth in frequency. The relationship between metabolic reprogramming and immune infiltration has been identified as having a crucial impact on HCC progression. However, a deeper understanding of the interplay between the immune system and metabolism in the HCC microenvironment is required. In this study, we used a proteomic dataset to identify three immune subtypes (IM1-IM3) in HCC, each of which has distinctive clinical, immune, and metabolic characteristics. Among these subtypes, IM3 was found to have the poorest prognosis, with the highest levels of immune infiltration and T-cell exhaustion. Furthermore, IM3 showed elevated glycolysis and reduced bile acid metabolism, which was strongly correlated with CD8 T cell exhaustion and regulatory T cell accumulation. Our study presents the proteomic immune stratification of HCC, revealing the possible link between immune cells and reprogramming of HCC glycolysis and bile acid metabolism, which may be a viable therapeutic strategy to improve HCC immunotherapy.

Metabolic and immune-related gene signatures: Predictive stratification and prognostic implications in gastric cancer.

BACKGROUND: Gastric cancer, marked by its heterogeneous nature, showcases various molecular subtypes and clinical trajectories. This research delves into the significance of metabolic and immune-driven pathways in gastric cancer, constructing a prognostic signature derived from differentially expressed metabolic and immune-correlated genes (DE-MIGs). METHODS: Metabolic and immune-associated gene were sourced from the GeneCards database. Differential expression analysis on the TCGA-STAD dataset was executed using the limma package, unveiling 51 DE-MIGs that underwent functional enrichment scrutiny. The LASSO Cox regression methodology guided the creation of the prognostic signature, and individual patient risk scores were determined. Assessment tools like CIBERSORT, ESTIMATE and ssGSEA were deployed to study the immune microenvironment, while mutation profiles, genomic stability, resistance to chemotherapy and immunotherapy responsiveness were scrutinized across distinct signature categorizations. RESULTS: Among the identified DE-MIGs, 26 were significantly tied to the overall survival of gastric cancer patients. The developed prognostic signature proficiently differentiated patients into high-risk and low-risk cohorts, with the latter showing markedly better outcomes. The study underscored the centrality of the immune microenvironment in influencing gastric cancer outcomes. Key pathways such as TGF-Beta, TP53 and NRF2 dominated the high-risk group, whereas the LRTK-RAS and WNT pathways characterized the low-risk group. Interestingly, the low-risk segment also manifested a heightened tumor mutation burden and enhanced susceptibility to immunotherapy. CONCLUSIONS: Our findings introduce a pivotal prognostic signature, rooted in DE-MIGs, that effectively segregates gastric cancer patients into distinct risk-based segments. Insights into the influential role of the immune microenvironment in gastric cancer progression pave the way for more refined therapeutic interventions.

Unveiling Immunological Signatures and Predictors of Response to Immunosuppressive Therapy in Acquired Aplastic Anaemia".

Acquired Aplastic Anaemia (AA) often results from immune destruction of hematopoietic stem and progenitor cells. However, only 60-70% of patients with AA respond to immunosuppressive therapy (IST). There is lack of strong predictive marker for response to IST which can help therapy. Our study sought to pinpoint unique immune markers in AA patients and validate established predictors for response to IST. We enrolled 51 severe AA patients and analyzed 57 immunological parameters via flow cytometry. Additionally, we measured paroxysmal nocturnal hemoglobinuria (PNH) clone, telomere length, and thrombopoietin (TPO) levels prior to IST. After a 6-months follow-up, response was observed. Patients with AA had a distinct immunological signature characterized by absolute lymphopenia, skewed CD4/CD8 ratio with expansion of CD8 T cells with activated and senescent phenotype. Treg counts were reduced, while proportion of Treg A and B was comparable to controls. Treatment response was correlated with elevated Absolute Neutrophil Count (ANC), Absolute Reticulocyte Count (ARC), and reduced CD57+ CD8+ naive cells and B cell % before therapy. However, predictors like TPO, telomere length, and PNH did not emerge as indicators of treatment response. Identifying predictors for treatment response in AA is challenging due to abnormal haematopoiesis, genetic mutations, and treatment variables.

Circulating immune signatures in chronic pancreatitis with and without preceding acute pancreatitis: A pilot study.

OBJECTIVE: To investigate profiles of circulating immune signatures in healthy controls and chronic pancreatitis patients (CP) with and without a preceding history of acute pancreatitis (AP). METHODS: We performed a phase 1, cross-sectional analysis of prospectively collected serum samples from the PROspective Evaluation of Chronic Pancreatitis for EpidEmiologic and Translation StuDies (PROCEED) study. All samples were collected during a clinically quiescent phase. CP subjects were categorized into two subgroups based on preceding episode(s) of AP. Healthy controls were included for comparison. Blinded samples were analyzed using an 80-plex Luminex assay of cytokines, chemokines, and adhesion molecules. Group and pairwise comparisons of analytes were performed between the subgroups. RESULTS: In total, 133 patients with CP (111 with AP and 22 without AP) and 50 healthy controls were included. Among the 80 analytes studied, CP patients with a history of AP had significantly higher serum levels of pro-inflammatory cytokines (interleukin (IL)-6, IL-8, IL-1 receptor antagonist, IL-15) and chemokines (Cutaneous T-Cell Attracting Chemokine (CTACK), Monokine induced Gamma Interferon (MIG), Macrophage-derived Chemokine (MDC), Monocyte Chemoattractant Protein-1 (MCP-1)) compared to CP without preceding AP and controls. In contrast, CP patients without AP had immune profiles characterized by low systemic inflammation and downregulation of anti-inflammatory mediators, including IL-10. CONCLUSION: CP patients with a preceding history of AP have signs of systemic inflammatory activity even during a clinically quiescent phase. In contrast, CP patients without a history of AP have low systemic inflammatory activity. These findings suggest the presence of two immunologically diverse subtypes of CP.

Lung immune signatures define two groups of end-stage IPF patients.

BACKGROUND: The role of the immune system in the pathobiology of Idiopathic Pulmonary Fibrosis (IPF) is controversial. METHODS: To investigate it, we calculated immune signatures with Gene Set Variation Analysis (GSVA) and applied them to the lung transcriptome followed by unbiased cluster analysis of GSVA immune-enrichment scores, in 109 IPF patients from the Lung Tissue Research Consortium (LTRC). Results were validated experimentally using cell-based methods (flow cytometry) in lung tissue of IPF patients from the University of Pittsburgh (n = 26). Finally, differential gene expression and hypergeometric test were used to explore non-immune differences between clusters. RESULTS: We identified two clusters (C#1 and C#2) of IPF patients of similar size in the LTRC dataset. C#1 included 58 patients (53%) with enrichment in GSVA immune signatures, particularly cytotoxic and memory T cells signatures, whereas C#2 included 51 patients (47%) with an overall lower expression of GSVA immune signatures (results were validated by flow cytometry with similar unbiased clustering generation). Differential gene expression between clusters identified differences in cilium, epithelial and secretory cell genes, all of them showing an inverse correlation with the immune response signatures. Notably, both clusters showed distinct features despite clinical similarities. CONCLUSIONS: In end-stage IPF lung tissue, we identified two clusters of patients with very different levels of immune signatures and gene expression but with similar clinical characteristics. Weather these immune clusters differentiate diverse disease trajectories remains unexplored.

Intravenous immunoglobulins, cyclosporine, and best supportive care in epidermal necrolysis: Diverse effects on systemic inflammation.

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but potentially life-threatening cutaneous adverse reactions. There is still no consensus on adjuvant treatments, and little is known about their effects on systemic inflammation in SJS/TEN. Our aim was to characterize the systemic and cutaneous immune profiles of SJS/TEN patients and to investigate whether/how intravenous immunoglobulins (IVIG), cyclosporine A (CSA), and best supportive care only (BSCO) affected the systemic immune signature and clinical outcome (6 week-mortality, complications, hospitalization stay). METHODS: We included 16 patients with SJS/TEN, treated with high-dose IVIG (n = 8), CSA (n = 4) or BSCO (n = 4). Serial serum samples were obtained prior-, 5-7 days, and 21 days after treatment onset. Serum levels of inflammation-/immune response-associated proteins were measured by high-throughput proteomics assay (OLINK) and cytotoxic molecules by ELISA. RNA extracted from skin biopsies collected prior treatment was analyzed by Nanostring. RESULTS: Serum inflammatory profiles in SJS/TEN patients were notably characterized by massive upregulation of type 1 immune response and proinflammatory markers. Surprisingly, there was limited overlap between cutaneous and serum immune profiles. Serial serological measurements of immune response markers showed very diverse dynamics between the different treatment groups. IVIG-treated patients showed completely different dynamics and most significant proteomic changes in an early phase (Day 5-7). In all treatment groups, type 1-/inflammatory response markers were dampened at day 21. Clinically, there were no outcome differences. CONCLUSION: Our study demonstrates that BSCO, CSA, and IVIG have very diverse biological effects on the systemic inflammatory response in SJS/TEN, which may not correlate with clinical outcome differences.

Subtyping of sarcomas based on pathway enrichment scores in bulk and single cell transcriptomes.

BACKGROUND: Sarcomas are highly heterogeneous in molecular, pathologic, and clinical features. However, a classification of sarcomas by integrating different types of pathways remains mostly unexplored. METHODS: We performed hierarchical clustering analysis of sarcomas based on the enrichment scores of 14 pathways involved in immune, stromal, DNA damage repair (DDR), and oncogenic signatures in three bulk tumor transcriptome datasets. RESULTS: Consistently in the three datasets, sarcomas were classified into three subtypes: Immune Class (Imm-C), Stromal Class (Str-C), and DDR Class (DDR-C). Imm-C had the strongest anti-tumor immune signatures and the lowest intratumor heterogeneity (ITH); Str-C showed the strongest stromal signatures, the highest genomic stability and global methylation levels, and the lowest proliferation potential; DDR-C had the highest DDR activity, expression of the cell cycle pathway, tumor purity, stemness scores, proliferation potential, and ITH, the most frequent TP53 mutations, and the worst survival. We further validated the stability and reliability of our classification method by analyzing a single cell RNA-Seq (scRNA-seq) dataset. Based on the expression levels of five genes in the pathways of T cell receptor signaling, cell cycle, mismatch repair, focal adhesion, and calcium signaling, we built a linear risk scoring model (ICMScore) for sarcomas. We demonstrated that ICMScore was an adverse prognostic factor for sarcomas and many other cancers. CONCLUSIONS: Our classification method provides novel insights into tumor biology and clinical implications for sarcomas.

eIF6 is potential diagnostic and prognostic biomarker that associated with 18F-FDG PET/CT features and immune signatures in esophageal carcinoma.

BACKGROUND: Although eukaryotic initiation factor 6 (eIF6) is a novel therapeutic target, data on its importance in the development of esophageal carcinoma (ESCA) remains limited. This study evaluated the correlation between eIF6 expression and metabolic analysis using fluorine-18 fluorodeoxyglucose (18F-FDG) -Positron emission tomography (PET) and immune gene signatures in ESCA. METHODS: This study employed The Cancer Genome Atlas (TCGA) to analyze the expression and prognostic value of eIF6, as well as its relationship with the immune gene signatures in ESCA patients. The qRT-PCR and Western blot analyses were used to profile the expression of eIF6 in ESCA tissues and different ESCA cell lines. The expression of tumor eIF6 and glucose transporter 1 (GLUT1) was examined using immunohistochemical tools in fifty-two ESCA patients undergoing routine 18F-FDG PET/CT before surgery. In addition, the cellular responses to eIF6 knockdown in human ESCA cells were assessed via the MTS, EdU, flow cytometry and wound healing assays. RESULTS: Our data demonstrated that compared with the normal esophageal tissues, eIF6 expression was upregulated in ESCA tumor tissues and showed a high diagnostic value with an area under curve of 0.825 for predicting ESCA. High eIF6 expression was significantly correlated with shorter overall survival of patients with esophagus adenocarcinoma (p = 0.038), but not in squamous cell carcinoma of the esophagus (p = 0.078). In addition, tumor eIF6 was significantly associated with 18F-FDG PET/CT parameters: maximal and mean standardized uptake values (SUVmax and SUVmean) and total lesion glycolysis (TLG) (rho = 0.458, 0.460, and 0.300, respectively, p < 0.01) as well as GLUT1 expression (rho = 0.453, p < 0.001). A SUVmax cutoff of 18.2 led to prediction of tumor eIF6 expression with an accuracy of 0.755. Functional analysis studies demonstrated that knockdown of eIF6 inhibited ESCA cell growth and migration, and fueled cell apoptosis. Moreover, the Bulk RNA gene analysis revealed a significant inverse association between eIF6 and the tumor-infiltrating immune cells (macrophages, T cells, or Th1 cells) and immunomodulators in the ESCA microenvironment. CONCLUSION: Our study suggested that eIF6 might serve as a potential prognostic biomarker associated with metabolic variability and immune gene signatures in ESCA tumor microenvironment.

The possible role of SRMS in colorectal cancer by bioinformatics analysis.

BACKGROUND: Src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristoylation sites (SRMS) is a non-receptor tyrosine kinase that has been found to be overexpressed in various tumors. However, the role of SRMS in colorectal cancer (CRC) has not been well established. METHODS: We evaluated the expression levels of SRMS in CRC using GEPIA, Oncomine, and HPA datasets. Survival information and gene expression data of CRC were obtained from The Cancer Genome Atlas (TCGA). Then, the association between SRMS and clinicopathological features was analyzed using UALCAN dataset. LinkedOmics was used to determine co-expression and functional networks associated with SRMS. Besides, we used TISIDB to assess the correlation between SRMS and immune signatures, including tumor-infiltrating immune cells and immunomodulators. Lastly, protein-protein interaction network (PPI) was established and the function enrichment analysis of the SRMS-associated immunomodulators and immune cell marker genes were performed using the STRING portal. RESULTS: Compared to normal colorectal tissues, SRMS was found to be overexpressed in CRC tissues, which was correlated with a poor prognosis. In colon adenocarcinoma (COAD), the expression levels of SRMS are significantly correlated with pathological stages and nodal metastasis status. Functional network analysis suggested that SRMS regulates intermediate filament-based processes, protein autophosphorylation, translational initiation, and elongation signaling through pathways involving ribosomes, proteasomes, oxidative phosphorylation, and DNA replication. In addition, SRMS expression was correlated with infiltrating levels of CD4+ T cells, CD56dim, MEM B, Neutrophils, Th2, Th17, and Act DC. The gene ontology (GO) analysis of SRMS-associated immunomodulators and immune cell marker genes showed that they were mainly enriched in the immune microenvironment molecule-related signals. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of these genes indicated that they are involved in multiple cancer-related pathways. CONCLUSIONS: SRMS is a promising prognostic biomarker and potential therapeutic target for CRC patients. In particular, SRMS regulates CRC progression by modulating cytokine-cytokine receptor interaction, chemokines, IL-17, and intestinal immune networks for IgA production signaling pathways among others. However, more studies are needed to validate these findings.

Deep abscopal response to radiotherapy and anti-PD-1 in an oligometastatic melanoma patient with unfavorable pretreatment immune signature.

Radiotherapy can elicit abscopal effects in non-irradiated metastases, particularly under immune checkpoint blockade (ICB). We report on two elderly patients with oligometastatic melanoma treated with anti-PD-1 and stereotactic body radiation therapy (SBRT). Before treatment, patient 1 showed strong tumor infiltration with exhausted CD8+ T cells and high expression of T cell-attracting chemokines. This patient rapidly mounted a complete response, now ongoing for more than 4.5 years. Patient 2 exhibited low CD8+ T cell infiltration and high expression of immunosuppressive arginase. After the first SBRT, his non-irradiated metastases did not regress and new metastases occurred although neoepitope-specific and differentiation antigen-specific CD8+ T cells were detected in the blood. A second SBRT after 10 months on anti-PD-1 induced a radiologic complete response correlating with an increase in activated PD-1-expressing CD8 T cells. Apart from a new lung lesion, which was also irradiated, this deep abscopal response lasted for more than 2.5 years. However, thereafter, his disease progressed and the activated PD-1-expressing CD8 T cells dropped. Our data suggest that oligometastatic patients, where a large proportion of the tumor mass can be irradiated, are good candidates to improve ICB responses by RT, even in the case of an unfavorable pretreatment immune signature, after progression on anti-PD-1, and despite advanced age. Besides repeated irradiation, T cell epitope-based immunotherapies (e.g., vaccination) may prolong antitumor responses even in patients with unfavorable pretreatment immune signature.

"Tumor immunology meets oncology (TIMO) XV", April 25th-27th 2019, Halle/Saale, Germany.

Novel insights into basic and translational tumor immunology including immunotherapies were presented by national and international scientists and clinicians at the TIMO XV meeting in Halle.

Comprehensive analysis and establishment of a prediction model of alternative splicing events reveal the prognostic predictor and immune microenvironment signatures in triple negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is widely concerning because of high malignancy and poor prognosis. There is increasing evidence that alternative splicing (AS) plays an important role in the development of cancer and the formation of the tumour microenvironment. However, comprehensive analysis of AS signalling in TNBC is still lacking and urgently needed. METHODS: Transcriptome and clinical data of 169 TNBC tissues and 15 normal tissues were obtained and integrated from the cancer genome atlas (TCGA), and an overview of AS events was downloaded from the SpliceSeq database. Then, differential comparative analysis was performed to obtain cancer-associated AS events (CAAS). Metascape was used to perform parent gene enrichment analysis based on CAAS. Unsupervised cluster analysis was performed to analyse the characteristics of immune infiltration in the microenvironment. A splicing network was established based on the correlation between CAAS events and splicing factors (SFs). We then constructed prediction models and assessed the accuracy of these models by receiver operating characteristic (ROC) curve and Kaplan-Meier survival analyses. Furthermore, a nomogram was adopted to predict the individualized survival rate of TNBC patients. RESULTS: We identified 1194 cancer-associated AS events (CAAS) and evaluated the enrichment of 981 parent genes. The top 20 parent genes with significant differences were mostly related to cell adhesion, cell component connection and other pathways. Furthermore, immune-related pathways were also enriched. Unsupervised clustering analysis revealed the heterogeneity of the immune microenvironment in TNBC. The splicing network also suggested an obvious correlation between SFs expression and CAAS events in TNBC patients. Univariate and multivariate Cox regression analyses showed that the survival-related AS events were detected, including some significant participants in the carcinogenic process. A nomogram incorporating risk, AJCC and radiotherapy showed good calibration and moderate discrimination. CONCLUSION: Our study revealed AS events related to tumorigenesis and the immune microenvironment, elaborated the potential correlation between SFs and CAAS, established a prognostic model based on survival-related AS events, and created a nomogram to better predict the individual survival rate of TNBC patients, which improved our understanding of the relationship between AS events and TNBC.

Correlate tumor mutation burden with immune signatures in human cancers.

BACKGROUND: Tumor mutation burden (TMB) has been associated with cancer immunotherapeutic response and cancer prognosis. Although many explorations have revealed that high TMB may yield many neoantigens to incite antitumor immune response, a systematic exploration of the correlation between TMB and immune signatures in different cancer types is lacking. RESULTS: We classified cancer into the lower-TMB subtype and the higher-TMB subtype for each of 32 cancer types based on their somatic mutation data from the Cancer Genome Atlas (TCGA), and compared the expression levels of immune-related genes and gene-sets between both subtypes of cancers in each cancer type. In some cancer types most of the immune signatures analyzed were upregulated in the lower-TMB subtype, while in some other cancer types the immune signatures were prone to be upregulated in the higher-TMB subtype. However, the regulatory T cells, immune cell infiltrate, tumor-infiltrating lymphocytes, and cytokine signatures tended to be upregulated in the lower-TMB subtype, and the cancer-testis antigen (CTA) and pro-inflammatory signatures were inclined to be upregulated in the higher-TMB subtype. Importantly, high TMB was associated with elevated expression of PD-L1 in diverse prevailing cancers. Furthermore, we found that higher TMB was associated with better survival prognosis in numerous cancer types while was associated with worse prognosis in a few cancer types. CONCLUSIONS: High TMB may inhibit immune cell infiltrations while promote CTAs expression and inflammatory response in cancer. In many common cancer types, higher TMB may respond favorably to anti-PD-1/PD-L1 immunotherapy. Our data implicate that higher-TMB patients could gain a more favorable prognosis in diverse cancer types if treated with immunotherapy, otherwise would have a poorer prognosis compared to lower-TMB patients.

A novel approach reveals that HLA class 1 single antigen bead-signatures provide a means of high-accuracy pre-transplant risk assessment of acute cellular rejection in renal transplantation.

BACKGROUND: Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. RESULTS: The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA < 30%) who showed detectable pre-transplant anti-HLA 1 antibodies. To assess whether the reactivity profiles provide a means for ACR risk assessment, we established a novel approach which differs from standard approaches in two aspects: the use of quantitative continuous data and the use of a multiparameter classification method. Remarkably, it achieved significant prediction of the 38 graft recipients who experienced ACR with a balanced accuracy of 82.7% (sensitivity = 76.5%, specificity = 88.9%). CONCLUSIONS: The resultant classifier achieved one of the highest prediction accuracies in the literature for pre-transplant risk assessment of ACR. Importantly, it can facilitate risk assessment in non-sensitized patients who lack donor-specific antibodies. As the classifier is based on continuous data and includes weak signals, our results emphasize that not only strong but also weak binding interactions of antibodies and HLA 1 antigens contain predictive information. TRIAL REGISTRATION: ClinicalTrials.gov NCT00724022 . Retrospectively registered July 2008.

Schlafen-11 expression is associated with immune signatures and basal-like phenotype in breast cancer.

PURPOSE: Breast cancer (BC) is a heterogeneous disorder, with variable response to systemic chemotherapy. Likewise, BC shows highly complex immune activation patterns, only in part reflecting classical histopathological subtyping. Schlafen-11 (SLFN11) is a nuclear protein we independently described as causal factor of sensitivity to DNA damaging agents (DDA) in cancer cell line models. SLFN11 has been reported as a predictive biomarker for DDA and PARP inhibitors in human neoplasms. SLFN11 has been implicated in several immune processes such as thymocyte maturation and antiviral response through the activation of interferon signaling pathway, suggesting its potential relevance as a link between immunity and cancer. In the present work, we investigated the transcriptional landscape of SLFN11, its potential prognostic value, and the clinico-pathological associations with its variability in BC. METHODS: We assessed SLFN11 determinants in a gene expression meta-set of 5061 breast cancer patients annotated with clinical data and multigene signatures. RESULTS: We found that 537 transcripts are highly correlated with SLFN11, identifying "immune response", "lymphocyte activation", and "T cell activation" as top Gene Ontology processes. We established a strong association of SLFN11 with stromal signatures of basal-like phenotype and response to chemotherapy in estrogen receptor negative (ER-) BC. We identified a distinct subgroup of patients, characterized by high SLFN11 levels, ER- status, basal-like phenotype, immune activation, and younger age. Finally, we observed an independent positive predictive role for SLFN11 in BC. CONCLUSIONS: Our findings are suggestive of a relevant role for SLFN11 in BC and its immune and molecular variability.

Altered CD4+ T cell immunity in nurses occupationally exposed to viral pathogens.

Pathogen exposure, including but not limited to herpesviruses, moulds the shape of the immune system, both at a basal state and in response to immune challenge. However, little is known about the impact of high exposure to other viruses on baseline immune signatures and how the immune system copes with repetitive exposures to maintain a balanced functionality. Here we investigated baseline immune signatures, including detailed T cell phenotyping, antigen-specific CD4+ and CD8+ T cell responses and cytokine profile in paediatric (PED) nurses, who have high occupational exposure to viral pathogens including varicella zoster virus (VZV) and respiratory viruses, and in neonatal intensive care unit (NICU) nurses, as a control group with infrequent occupational exposure. Our results show a lower CD4+ T cell response to two VZV proteins (IE62 and gE) and to tetanus toxoid (TT) in PED nurses who are cytomegalovirus (CMV)-seronegative, compared to CMV-seronegative NICU nurses, and that the decline might be more pronounced the more sustained the exposure. This decline might be due to an attrition of VZV- and TT-specific T cells as a result of the continuous pressure on the CD4+ T cell compartment. Moreover, our data suggest that the distinct T cell phenotypes known to be associated with CMV-seropositivity might be less prominent in PED nurses compared to NICU nurses, implying a plausible attenuating effect of occupational exposure on CMV-associated immunosenescence. Overall, this pilot study reveals an impact of occupational exposure to viral pathogens on CD4+ T cell immunity and supports further investigation in a larger cohort.

Stratification of Latent Mycobacterium tuberculosis Infection by Cellular Immune Profiling.

Background: Recently acquired and remotely acquired latent Mycobacterium tuberculosis infection (LTBI) are clinically indistinguishable, yet recent acquisition of infection is the greatest risk factor for progression to tuberculosis in immunocompetent individuals. We aimed to evaluate the ability of cellular immune signatures that differ between active tuberculosis and LTBI to distinguish recently from remotely acquired LTBI. Methods: Fifty-nine individuals were recruited: 20 had active tuberculosis, 19 had recently acquired LTBI, and 20 had remotely acquired LTBI. The proportion of mycobacteria-specific CD4+ T cells secreting tumor necrosis factor α (TNF-α) but not interferon γ or interleukin 2 which had a differentiated effector phenotype (TNF-α-only TEFF), and the level of CD27 expression on IFN-γ-producing CD4+ T cells, were detected by flow cytometry. Results: The TNF-α-only TEFF signature was significantly higher in the group with recently acquired LTBI, compared with the group with remotely acquired LTBI (P < .0001), and it discriminated between these groups with high sensitivity and specificity, with an area under the curve of 0.87. Two signatures incorporating CD27 expression did not distinguish between recently and remotely acquired LTBI. Interestingly, the TNF-α-only TEFF signature in participants with recently acquired LTBI was more similar to that in participants with tuberculosis than that in participants with remotely acquired LTBI, suggesting that recently acquired LTBI is immunologically more similar to tuberculosis than remotely acquired LTBI. Conclusions: These findings reveal marked biological heterogeneity underlying the clinically homogeneous phenotype of LTBI, providing a rationale for immunological risk stratification to improve targeting of LTBI treatment.

Subtype-specific prognostic impact of different immune signatures in node-negative breast cancer.

BACKGROUND: The role of different subtypes of immune cells is still a matter of debate. METHODS: We compared the prognostic relevance for metastasis-free survival (MFS) of a B-cell signature (BS), a T-cell signature (TS), and an immune checkpoint signature (CPS) in node-negative breast cancer (BC) using mRNA expression. Microarray-based gene-expression data were analyzed in six previously published cohorts of node-negative breast cancer patients not treated with adjuvant therapy (n = 824). The prognostic relevance of the individual immune markers was assessed using univariate analysis. The amount of independent prognostic information provided by each immune signature was then compared using a likelihood ratio statistic in the whole cohort as well as in different molecular subtypes. RESULTS: Univariate Cox regression in the whole cohort revealed prognostic significance of CD4 (HR 0.66, CI 0.50-0.87, p = 0.004), CXCL13 (HR 0.86, CI 0.81-0.92, p < 0.001), CD20 (HR 0.76, CI 0.64-0.89, p = 0.001), IgκC (HR 0.81, CI 0.75-0.88, p < 0.001), and CTLA-4 (HR 0.67, CI 0.46-0.97, p = 0.032). Multivariate analyses of the immune signatures showed that both TS (p < 0.001) and BS (p < 0.001) showed a significant prognostic information in the whole cohort. After accounting for clinical-pathological variables, TS (p < 0.001), BS (p < 0.05), and CPS (p < 0.05) had an independent effect for MFS. In subgroup analyses, the prognostic effect of immune cells was most pronounced in HER2+ BC: BS as well as TS showed a strong association with MFS when included first in the model (p < 0.001). CONCLUSION: Immune signatures provide subtype-specific additional prognostic information over clinical-pathological variables in node-negative breast cancer.

Integrated evaluation of PAM50 subtypes and immune modulation of pCR in HER2-positive breast cancer patients treated with chemotherapy and HER2-targeted agents in the CherLOB trial.

BACKGROUND: The aim of this work was to evaluate the impact of (and relative contribution of) tumor-related and immune-related diversity of HER2-positive disease on the response to neoadjuvant chemotherapy plus anti-HER2 agents. PATIENTS AND METHODS: The CherLOB phase II study randomized 121 HER2-positive breast cancer patients to neoadjuvant chemotherapy plus trastuzumab, lapatinib or both. Tumor samples from diagnostic core biopsy were centralized. Tumor-infiltrating lymphocytes (TILs) were evaluated on H&E slides. Intrinsic subtyping was carried out using the research-based 50-gene prediction analysis of a microarray (PAM50) subtype predictor. Immune-related gene signatures were also evaluated. RESULTS: Continuous Str-TILs and It-TILs were significantly associated with pCR [OR 1.03, 95% CI 1.02-1.05 (P < 0.001) and OR 1.09, 95% CI 1.04-1.15 (P < 0.001) for Str-TILs and It-TILs, respectively]. According to PAM50, the subtype distribution was as follows: HER2-enriched 26.7%, Luminal A 25.6%, Luminal B 16.3%, Basal-like 14% and Normal-like 17.4%. The highest rate of pCR was observed for the HER2-enriched subtype (50%), followed by Basal-like, Luminal B and Luminal A (χ(2) test, P = 0.026). Immune gene signatures significantly associated with pCR in univariate analyses were identified: most of them maintained a significant association with pCR in multivariate analyses corrected for PAM50 subtypes, whereas TILs did not. CONCLUSIONS: In this study, both tumor-related and immune-related features contribute to the modulation of pCR after neoadjuvant chemotherapy plus anti-HER2 agents. Immune signatures rather than TILs added significant prediction of pCR beyond PAM50 intrinsic subtypes.

Conservation of immune gene signatures in solid tumors and prognostic implications.

BACKGROUND: Tumor-infiltrating leukocytes can either limit cancer growth or facilitate its spread. Diagnostic strategies that comprehensively assess the functional complexity of tumor immune infiltrates could have wide-reaching clinical value. In previous work we identified distinct immune gene signatures in breast tumors that reflect the relative abundance of infiltrating immune cells and exhibited significant associations with patient outcomes. Here we hypothesized that immune gene signatures agnostic to tumor type can be identified by de novo discovery of gene clusters enriched for immunological functions and possessing internal correlation structure conserved across solid tumors from different anatomic sites. METHODS: We assembled microarray expression datasets encompassing 5,295 tumors of the breast, colon, lung, ovarian and prostate. Unsupervised clustering methods were used to determine number and composition of gene clusters within each dataset. Immune-enriched gene clusters (signatures) identified by gene ontology enrichment were analyzed for internal correlation structure and conservation across tumors then compared against expression profiles of: 1) flow-sorted leukocytes from peripheral blood and 2) >300 cancer cell lines from solid and hematologic cancers. Cox regression analysis was used to identify signatures with significant associations with clinical outcome. RESULTS: We identified nine distinct immune-enriched gene signatures conserved across all five tumor types. The signatures differentiated specific leukocyte lineages with moderate discernment overall, and naturally organized into six discrete groups indicative of admixed lineages. Moreover, seven of the signatures exhibit minimal and uncorrelated expression in cancer cell lines, suggesting that these signatures derive predominantly from infiltrating immune cells. All nine immune signatures achieved statistically significant associations with patient prognosis (p<0.05) in one or more tumor types with greatest significance observed in breast and skin cancers. Several signatures indicative of myeloid lineages exhibited poor outcome associations that were most apparent in brain and colon cancers. CONCLUSIONS: These findings suggest that tumor infiltrating immune cells can be differentiated by immune-specific gene expression patterns that quantify the relative abundance of multiple immune infiltrates across a range of solid tumor types. That these markers of immune involvement are significantly associated with patient prognosis in diverse cancers suggests their clinical utility as pan-cancer markers of tumor behavior and immune responsiveness.