The transcriptomic expression pattern of immune checkpoints shows heterogeneity between and within cancer types.

Transcriptomic expression profiles of immune checkpoint markers are of interest in order to decipher the mechanisms of immunotherapy response and resistance. Overall, 514 patients with various solid tumors were retrospectively analyzed in this study. The RNA expression levels of tumor checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) were ranked from 0-100 percentile based on a reference population. The expression of each checkpoint was correlated with cancer type, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) by immunohistochemistry (IHC). The cohort included 30 different tumor types, with colorectal cancer being the most common (27%). When RNA percentile rank values were categorized as "Low" (0-24), "Intermediate" (25-74), and "High" (75-100), each patient had a distinctive portfolio of the categorical expression of 16 checkpoint markers. Association between some checkpoint markers and cancer types were observed; NOS2 showed significantly higher expression in colorectal and stomach cancer (P < 0.001). Principal component analysis demonstrated no clear association between combined RNA expression patterns of 16 checkpoint markers and cancer types, TMB, MSI or PD-L1 IHC. Immune checkpoint RNA expression varies from patient to patient, both within and between tumor types, though colorectal and stomach cancer showed the highest levels of NOS2, a mediator of inflammation and immunosuppression. There were no specific combined expression patterns correlated with MSI, TMB or PD-L1 IHC. Next generation immunotherapy trials may benefit from individual analysis of patient tumors as selection criteria for specific immunomodulatory approaches.

Cancer-Immunity Marker RNA Expression Levels across Gynecologic Cancers: Implications for Immunotherapy.

Our objective was to characterize cancer-immunity marker expression in gynecologic cancers and compare immune landscapes between gynecologic tumor subtypes and with nongynecologic solid tumors. RNA expression levels of 51 cancer-immunity markers were analyzed in patients with gynecologic cancers versus nongynecologic cancers, and normalized to a reference population of 735 control cancers, ranked from 0 to 100, and categorized as low (0-24), moderate (25-74), or high (75-100) percentile rank. Of the 72 patients studied, 43 (60%) had ovarian, 24 (33%) uterine, and 5 (7%) cervical cancer. No two immune profiles were identical according to expression rank (0-100) or rank level (low, moderate, or high). Patients with cervical cancer had significantly higher expression level ranks of immune activating, proinflammatory, tumor-infiltrating lymphocyte markers, and checkpoints than patients with uterine or ovarian cancer (P < 0.001 for all comparisons). However, there were no significant differences in immune marker expression between uterine and ovarian cancers. Tumors with PD-L1 tumor proportional score (TPS) ≥1% versus 0% had significantly higher expression levels of proinflammatory markers (58 vs. 49%, P = 0.0004). Compared to patients with nongynecologic cancers, more patients with gynecologic cancers express high levels of IDO-1 (44 vs. 13%, P < 0.001), LAG3 (35 vs. 21%, P = 0.008), and IL10 (31 vs. 15%, P = 0.002.) Patients with gynecologic cancers have complex and heterogeneous immune landscapes that are distinct from patient to patient and from other solid tumors. High levels of IDO1 and LAG3 suggest that clinical trials with IDO1 inhibitors or LAG3 inhibitors, respectively, may be warranted in gynecologic cancers.

T-cell priming transcriptomic markers: implications of immunome heterogeneity for precision immunotherapy.

Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.

A transcriptomics approach to expand therapeutic options and optimize clinical trials in oncology.

Background: The current model of clinical drug development in oncology displays major limitations due to a high attrition rate in patient enrollment in early phase trials and a high failure rate of drugs in phase III studies. Objective: Integrating transcriptomics for selection of patients has the potential to achieve enhanced speed and efficacy of precision oncology trials for any targeted therapies or immunotherapies. Methods: Relative gene expression level in the metastasis and normal organ-matched tissues from the WINTHER database was used to estimate in silico the potential clinical benefit of specific treatments in a variety of metastatic solid tumors. Results: As example, high mRNA expression in tumor tissue compared to analogous normal tissue of c-MET and its ligand HGF correlated in silico with shorter overall survival (OS; p < 0.0001) and may constitute an independent prognostic marker for outcome of patients with metastatic solid tumors, suggesting a strategy to identify patients most likely to benefit from MET-targeted treatments. The prognostic value of gene expression of several immune therapy targets (PD-L1, CTLA4, TIM3, TIGIT, LAG3, TLR4) was investigated in non-small-cell lung cancers and colorectal cancers (CRCs) and may be useful to optimize the development of their inhibitors, and opening new avenues such as use of anti-TLR4 in treatment of patients with metastatic CRC. Conclusion: This in silico approach is expected to dramatically decrease the attrition of patient enrollment and to simultaneously increase the speed and detection of early signs of efficacy. The model may significantly contribute to lower toxicities. Altogether, our model aims to overcome the limits of current approaches.

BORIS/CTCFL-mediated chromatin accessibility alterations promote a pro-invasive transcriptional signature in melanoma cells.

Melanoma is the deadliest form of skin cancer, due to its tendency to metastasize early. Brother of regulator of imprinted sites (BORIS), also known as CCCTC binding factor-like (CTCFL), is a transcription regulator that becomes ectopically expressed in melanoma. We recently showed that BORIS contributes to melanoma phenotype switching by altering the gene expression program of melanoma cells from an intermediate melanocytic state toward a more mesenchymal-like state. However, the mechanism underlying this transcriptional switch remains unclear. Here, ATAC-seq was used to study BORIS-mediated chromatin accessibility alterations in melanoma cells harboring an intermediate melanocytic state. The gene set that gained promoter accessibility, following ectopic BORIS expression, showed enrichment for biological processes associated with melanoma invasion, while promoters of genes associated with proliferation showed reduced accessibility. Integration of ATAC-seq and RNA-seq data demonstrated that increased chromatin accessibility was associated with transcriptional upregulation of genes involved in tumor progression processes, and the aberrant activation of oncogenic transcription factors, while reduced chromatin accessibility and downregulated genes were associated with repressed activity of tumor suppressors and proliferation factors. Together, these findings indicate that BORIS mediates transcriptional reprogramming in melanoma cells by altering chromatin accessibility and gene expression, shifting the cellular transcription landscape of melanoma cells toward a mesenchymal-like genetic signature.

Autism spectrum disorder diagnosis using a new panel of immune- and inflammatory-related serum biomarkers: A case-control multicenter study.

Background and objectives: Children with autism spectrum disorder (ASD) present with distinctive clinical features. No objective laboratory assay has been developed to establish a diagnosis of ASD. Considering the known immunological associations with ASD, immunological biomarkers might enable ASD diagnosis and intervention at an early age when the immature brain has the highest degree of plasticity. This work aimed to identify diagnostic biomarkers discriminating between children with ASD and typically developing (TD) children. Methods: A multicenter, diagnostic case-control study trial was conducted in Israel and Canada between 2014 and 2021. In this trial, a single blood sample was collected from 102 children with ASD as defined in Diagnostic Statistical Manual of Mental Disorders [DSM)-IV (299.00) or DSM-V (299.00)], and from 97 typically developing control children aged 3-12 years. Samples were analyzed using a high-throughput, multiplexed ELISA array which quantifies 1,000 human immune/inflammatory-related proteins. Multiple logistic regression analysis was used to obtain a predictor from these results using 10-fold cross validation. Results: Twelve biomarkers were identified that provided an overall accuracy of 0.82 ± 0.09 (sensitivity: 0.87 ± 0.08; specificity: 0.77 ± 0.14) in diagnosing ASD with a threshold of 0.5. The resulting model had an area under the curve of 0.86 ± 0.06 (95% CI: 0.811-0.889). Of the 102 ASD children included in the study, 13% were negative for this signature. Most of the markers included in all models have been reported to be associated with ASD and/or autoimmune diseases. Conclusion: The identified biomarkers may serve as the basis of an objective assay for early and accurate diagnosis of ASD. In addition, the markers may shed light on ASD etiology and pathogenesis. It should be noted that this was only a pilot, case-control diagnostic study, with a high risk of bias. The findings should be validated in larger prospective cohorts of consecutive children suspected of ASD.

Cancer immunity marker RNA expression levels across gynecologic cancers: Implications for immunotherapy.

Background: Our objective was to characterize cancer immunity marker expression in gynecologic cancers and compare immune landscapes between gynecologic tumor subtypes and with non-gynecologic solid tumors. Methods: RNA expression levels of 51 cancer-immunity markers were analyzed in patients with gynecologic cancers vs. non-gynecologic cancers, and normalized to a reference population of 735 control cancers, ranked from 0-100, and categorized as low (0-24), moderate (25-74), or high (75-100) percentile rank. Results: Of the 72 patients studied, 43 (60%) had ovarian, 24 (33%) uterine, and 5 (7%) cervical cancer. No two immune profiles were identical according to expression rank (0-100) or rank level (low, moderate, or high). Patients with cervical cancer had significantly higher expression level ranks of immune activating, pro-inflammatory, tumor infiltrating lymphocyte markers and checkpoints than patients with uterine or ovarian cancer (p<0.001 for all comparisons). However, there were no significant differences in immune marker expression between uterine and ovarian cancers. Tumors with PD-L1 TPS =>1% versus 0% had significantly higher expression levels of pro-inflammatory markers (58 vs. 49%, p=0.0004). Compared to patients with non-gynecologic cancers, more patients with gynecologic cancers express high levels of IDO-1 (44 vs. 13%, p<0.001), LAG3 (35 vs. 21%, p=0.008) and IL10 (31 vs. 15%, p=0.002.) Conclusions: Patients with gynecologic cancers have complex and heterogeneous immune landscapes that are distinct from patient to patient and from other solid tumors. High levels of IDO1 and LAG3 suggest that clinical trials with IDO1 inhibitors or LAG3 inhibitors, respectively, may be warranted in gynecologic cancers.

Comorbidity between lung cancer and COVID-19 pneumonia: role of immunoregulatory gene transcripts in high ACE2-expressing normal lung.

Background: SARS-CoV-2 (COVID-19) elicits a T-cell antigen-mediated immune response of variable efficacy. To understand this variability, we explored transcriptomic expression of angiotensin-converting enzyme 2 (ACE2, the SARS-CoV-2 receptor) and of immunoregulatory genes in normal lung tissues from patients with non-small cell lung cancer (NSCLC). Methods: This study used the transcriptomic and the clinical data for NSCLC patients generated during the CHEMORES study [n = 123 primary resected (early-stage) NSCLC] and the WINTHER clinical trial (n = 32 metastatic NSCLC). Results: We identified patient subgroups with high and low ACE2 expression (p = 1.55 × 10-19) in normal lung tissue, presumed to be at higher and lower risk, respectively, of developing severe COVID-19 should they become infected. ACE2 transcript expression in normal lung tissues (but not in tumor tissue) of patients with NSCLC was higher in individuals with more advanced disease. High-ACE2 expressors had significantly higher levels of CD8+ cytotoxic T lymphocytes and natural killer cells but with presumably impaired function by high Thymocyte Selection-Associated High Mobility Group Box Protein TOX (TOX) expression. In addition, immune checkpoint-related molecules - PD-L1, CTLA-4, PD-1, and TIGIT - are more highly expressed in normal (but not tumor) lung tissues; these molecules might dampen immune response to either viruses or cancer. Importantly, however, high inducible T-cell co-stimulator (ICOS), which can amplify immune and cytokine reactivity, significantly correlated with high ACE2 expression in univariable analysis of normal lung (but not lung tumor tissue). Conclusions: We report a normal lung immune-tolerant state that may explain a potential comorbidity risk between two diseases - NSCLC and susceptibility to COVID-19 pneumonia. Further, a NSCLC patient subgroup has normal lung tissue expressing high ACE2 and high ICOS transcripts, the latter potentially promoting a hyperimmune response, and possibly leading to severe COVID-19 pulmonary compromise.

Projection of Expression Profiles to Transcription Factor Activity Space Provides Added Information.

Acute myeloid leukemia (AML) is an aggressive type of leukemia, characterized by the accumulation of highly proliferative blasts with a disrupted myeloid differentiation program. Current treatments are ineffective for most patients, partly due to the genetic heterogeneity of AML. This is driven by genetically distinct leukemia stem cells, resulting in relapse even after most of the tumor cells are destroyed. Thus, personalized treatment approaches addressing cellular heterogeneity are urgently required. Reconstruction of Transcriptional regulatory Networks (RTN) is a tool for inferring transcriptional activity in patients with various diseases. In this study, we applied this method to transcriptome profiles of AML patients to test if it provided additional information for the interpretation of transcriptome data. We showed that when RTN results were added to RNA-seq results, superior clusters were formed, which were more homogenous and allowed the better separation of patients with low and high survival rates. We concluded that the external knowledge used for RTN analysis improved the ability of unsupervised machine learning to find meaningful patterns in the data.

Transcriptomics in Tumor and Normal Lung Tissues Identify Patients With Early-Stage Non-Small-Cell Lung Cancer With High Risk of Postsurgery Recurrence Who May Benefit From Adjuvant Therapies.

PURPOSE: The prognosis of patients with non-small-cell lung cancer (NSCLC), traditionally determined by anatomic histology and TNM staging, neglects the biological features of the tumor that may be important in determining patient outcome and guiding therapeutic interventions. Identifying patients with NSCLC at increased risk of recurrence after curative-intent surgery remains an important unmet need so that known effective adjuvant treatments can be offered to those at highest risk of recurrence. METHODS: Relative gene expression level in the primary tumor and normal bronchial tissues was used to retrospectively assess their association with disease-free survival (DFS) in a cohort of 120 patients with NSCLC who underwent curative-intent surgery. RESULTS: Low versus high Digital Display Precision Predictor (DDPP) score (a measure of relative gene expression) was significantly associated with shorter DFS (highest recurrence risk; P = .006) in all patients and in patients with TNM stages 1-2 (P = .00051; n = 83). For patients with stages 1-2 and low DDPP score (n = 29), adjuvant chemotherapy was associated with improved DFS (P = .0041). High co-overexpression of CTLA-4, PD-L1, and ICOS in normal lung (28 of 120 patients) was also significantly associated with decreased DFS (P = .0013), suggesting an immune tolerance to tumor neoantigens in some patients. Patients with DDPP low and immunotolerant normal tissue had the shortest DFS (P = 2.12E-11). CONCLUSION: TNM stage, DDPP score, and immune competence status of normal lung are independent prognostic factors in multivariate analysis. Our findings open new avenues for prospective prognostic assessment and treatment assignment on the basis of transcriptomic profiling of tumor and normal lung tissue in patients with NSCLC.

A WIN Consortium phase I study exploring avelumab, palbociclib, and axitinib in advanced non-small cell lung cancer.

BACKGROUND: The Worldwide Innovative Network (WIN) Consortium has developed the Simplified Interventional Mapping System (SIMS) to better define the cancer molecular milieu based on genomics/transcriptomics from tumor and analogous normal tissue biopsies. SPRING is the first trial to assess a SIMS-based tri-therapy regimen in advanced non-small cell lung cancer (NSCLC). METHODS: Patients with advanced NSCLC (no EGFR, ALK, or ROS1 alterations; PD-L1 unrestricted; ≤2 prior therapy lines) received avelumab, axitinib, and palbociclib (3 + 3 dose escalation design). RESULTS: Fifteen patients were treated (five centers, four countries): six at each of dose levels 1 (DL1) and DL2; three at DL3. The most common ≥Grade 3 adverse events were neutropenia, hypertension, and fatigue. The recommended Phase II dose (RP2D) was DL1: avelumab 10 mg/kg IV q2weeks, axitinib 3 mg po bid, and palbociclib 75 mg po daily (7 days off/21 days on). Four patients (27%) achieved a partial response (PR) (progression-free survival [PFS]: 14, 24, 25 and 144+ weeks), including two after progression on pembrolizumab. Four patients attained stable disease (SD) that lasted ≥24 weeks: 24, 27, 29, and 64 weeks. At DL1 (RP2D), four of six patients (66%) achieved stable disease (SD) ≥6 months/PR (2 each). Responders included patients with no detectable PD-L1 expression and low tumor mutational burden. CONCLUSIONS: Overall, eight of 15 patients (53%) achieved clinical benefit (SD ≥ 24 weeks/PR) on the avelumab, axitinib, and palbociclib combination. This triplet showed antitumor activity in NSCLC, including in tumors post-pembrolizumab progression, and was active at the RP2D, which was well tolerated. NCT03386929 clinicaltrial.gov.

Results of an early second PCR test performed on SARS-CoV-2 positive patients may support risk assessment for severe COVID-19.

Identifying patients at increased risk for severe COVID-19 is of high priority during the pandemic as it could affect clinical management and shape public health guidelines. In this study we assessed whether a second PCR test conducted 2-7 days after a SARS-CoV-2 positive test could identify patients at risk for severe illness. Analysis of a nationwide electronic health records data of 1683 SARS-CoV-2 positive individuals indicated that a second negative PCR test result was associated with lower risk for severe illness compared to a positive result. This association was seen across different age groups and clinical settings. More importantly, it was not limited to recovering patients but also observed in patients who still had evidence of COVID-19 as determined by a subsequent positive PCR test. Our study suggests that an early second PCR test may be used as a supportive risk-assessment tool to improve disease management and patient care.

Synthetic lethality-mediated precision oncology via the tumor transcriptome.

Precision oncology has made significant advances, mainly by targeting actionable mutations in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome to guide patient treatment. Here, we introduce SELECT (synthetic lethality and rescue-mediated precision oncology via the transcriptome), a precision oncology framework harnessing genetic interactions to predict patient response to cancer therapy from the tumor transcriptome. SELECT is tested on a broad collection of 35 published targeted and immunotherapy clinical trials from 10 different cancer types. It is predictive of patients' response in 80% of these clinical trials and in the recent multi-arm WINTHER trial. The predictive signatures and the code are made publicly available for academic use, laying a basis for future prospective clinical studies.

Digital Display Precision Predictor: the prototype of a global biomarker model to guide treatments with targeted therapy and predict progression-free survival.

The expanding targeted therapy landscape requires combinatorial biomarkers for patient stratification and treatment selection. This requires simultaneous exploration of multiple genes of relevant networks to account for the complexity of mechanisms that govern drug sensitivity and predict clinical outcomes. We present the algorithm, Digital Display Precision Predictor (DDPP), aiming to identify transcriptomic predictors of treatment outcome. For example, 17 and 13 key genes were derived from the literature by their association with MTOR and angiogenesis pathways, respectively, and their expression in tumor versus normal tissues was associated with the progression-free survival (PFS) of patients treated with everolimus or axitinib (respectively) using DDPP. A specific eight-gene set best correlated with PFS in six patients treated with everolimus: AKT2, TSC1, FKB-12, TSC2, RPTOR, RHEB, PIK3CA, and PIK3CB (r = 0.99, p = 5.67E-05). A two-gene set best correlated with PFS in five patients treated with axitinib: KIT and KITLG (r = 0.99, p = 4.68E-04). Leave-one-out experiments demonstrated significant concordance between observed and DDPP-predicted PFS (r = 0.9, p = 0.015) for patients treated with everolimus. Notwithstanding the small cohort and pending further prospective validation, the prototype of DDPP offers the potential to transform patients' treatment selection with a tumor- and treatment-agnostic predictor of outcomes (duration of PFS).

High levels of LINE-1 transposable elements expressed in Kaposi's sarcoma-associated herpesvirus-related primary effusion lymphoma.

Kaposi's sarcoma-associated herpesvirus (KSHV, HHV-8) is a gamma herpesvirus associated with several human malignancies. Transposable elements (TEs) are ubiquitous in eukaryotic genomes, occupying about 45% of the human genome. TEs have been linked with a variety of disorders and malignancies, though the precise nature of their contribution to many of them has yet to be elucidated. Global transcriptome analysis for differentially expressed TEs in KSHV-associated primary effusion lymphoma (PEL) cells (BCBL1 and BC3) revealed large number of differentially expressed TEs. These differentially expressed TEs include LTR transposons, long interspersed nuclear elements (LINEs), and short interspersed nuclear elements (SINEs). Further analysis of LINE-1 (L1) elements revealed expression upregulation, hypo-methylation, and transition into open chromatin in PEL. In agreement with high L1 expression, PEL cells express ORF1 protein and possess high reverse transcriptase (RT)-activity. Interestingly, inhibition of this RT-activity suppressed PEL cell growth. Collectively, we identified high expression of TEs, and specifically of L1 as a critical component in the proliferation of PEL cells. This observation is relevant for the treatment of KSHV-associated malignancies since they often develop in AIDS patients that are treated with RT inhibitors with potent inhibition for both HIV and L1 RT activity.

Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination.

One important question in aging research is how differences in genomics and transcriptomics determine the maximum lifespan in various species. Despite recent progress, much is still unclear on the topic, partly due to the lack of samples in nonmodel organisms and due to challenges in direct comparisons of transcriptomes from different species. The novel ranking-based method that we employ here is used to analyze gene expression in the gray whale and compare its de novo assembled transcriptome with that of other long- and short-lived mammals. Gray whales are among the top 1% longest-lived mammals. Despite the extreme environment, or maybe due to a remarkable adaptation to its habitat (intermittent hypoxia, Arctic water, and high pressure), gray whales reach at least the age of 77 years. In this work, we show that long-lived mammals share common gene expression patterns between themselves, including high expression of DNA maintenance and repair, ubiquitination, apoptosis, and immune responses. Additionally, the level of expression for gray whale orthologs of pro- and anti-longevity genes found in model organisms is in support of their alleged role and direction in lifespan determination. Remarkably, among highly expressed pro-longevity genes many are stress-related, reflecting an adaptation to extreme environmental conditions. The conducted analysis suggests that the gray whale potentially possesses high resistance to cancer and stress, at least in part ensuring its longevity. This new transcriptome assembly also provides important resources to support the efforts of maintaining the endangered population of gray whales.

Direct comparison shows that mRNA-based diagnostics incorporate information which cannot be learned directly from genomic mutations.

BACKGROUND: Compared to the many uses of DNA-level testing in clinical oncology, development of RNA-based diagnostics has been more limited. An exception to this trend is the growing use of mRNA-based methods in early-stage breast cancer. Although DNA and mRNA are used together in breast cancer research, the distinct contribution of mRNA beyond that of DNA in clinical challenges has not yet been directly assessed. We hypothesize that mRNA harbors prognostically useful information independently of genomic variation. To validate this, we use both genomic mutations and gene expression to predict five-year breast cancer recurrence in an integrated test model. This is accomplished first by comparing the feature importance of DNA and mRNA features in a model trained on both, and second, by evaluating the difference in performance of models trained on DNA and mRNA data separately. RESULTS: We find that models trained on DNA and mRNA data give more weight to mRNA features than to DNA features, and models trained only on mRNA outperform models trained on DNA alone. CONCLUSIONS: The evaluation process presented here may serve as a framework for the interpretation of the relative contribution of individual molecular markers. It also suggests that mRNA has a distinct contribution in a diagnostic setting, beyond and independently of DNA mutation data.

Identification of Tumor Antigens in the HLA Peptidome of Patient-derived Xenograft Tumors in Mouse.

Personalized cancer immunotherapy targeting patient-specific cancer/testis antigens (CTA) and neoantigens may benefit from large-scale tumor human leukocyte antigen (HLA) peptidome (immunopeptidome) analysis, which aims to accurately identify antigens presented by tumor cells. Although significant efforts have been invested in analyzing the HLA peptidomes of fresh tumors, it is often impossible to obtain sufficient volumes of tumor tissues for comprehensive HLA peptidome characterization. This work attempted to overcome some of these obstacles by using patient-derived xenograft tumors (PDX) in mice as the tissue sources for HLA peptidome analysis. PDX tumors provide a proxy for the expansion of the patient tumor by re-grafting them through several passages to immune-compromised mice. The HLA peptidomes of human biopsies were compared with those derived from PDX tumors. Larger HLA peptidomes were obtained from the significantly larger PDX tumors as compared with the patient biopsies. The HLA peptidomes of different PDX tumors derived from the same source tumor biopsy were very reproducible, even following subsequent passages to new naïve mice. Many CTA-derived HLA peptides were discovered, as well as several potential neoantigens/variant sequences. Taken together, the use of PDX tumors for HLA peptidome analysis serves as a highly expandable and stable source of reproducible and authentic peptidomes, opening up new opportunities for defining large HLA peptidomes when only small tumor biopsies are available. This approach provides a large source for tumor antigens identification, potentially useful for personalized immunotherapy.

BORIS/CTCFL promotes a switch from a proliferative towards an invasive phenotype in melanoma cells.

Melanoma is among the most aggressive cancers due to its tendency to metastasize early. Phenotype switching between a proliferative and an invasive state has been suggested as a critical process for metastasis, though the mechanisms that regulate state transitions are complex and remain poorly understood. Brother of Regulator of Imprinted Sites (BORIS), also known as CCCTC binding factor-Like (CTCFL), is a transcriptional modulator that becomes aberrantly expressed in melanoma. Yet, the role of BORIS in melanoma remains elusive. Here, we show that BORIS is involved in melanoma phenotype switching. Genetic modification of BORIS expression in melanoma cells combined with whole-transcriptome analysis indicated that BORIS expression contributes to an invasion-associated transcriptome. In line with these findings, inducible BORIS overexpression in melanoma cells reduced proliferation and increased migration and invasion, demonstrating that the transcriptional switch is accompanied by a phenotypic switch. Mechanistically, we reveal that BORIS binds near the promoter of transforming growth factor-beta 1 (TFGB1), a well-recognized factor involved in the transition towards an invasive state, which coincided with increased expression of TGFB1. Overall, our study indicates a pro-invasive role for BORIS in melanoma via transcriptional reprogramming.

PICOT binding to chromatin-associated EED negatively regulates cyclin D2 expression by increasing H3K27me3 at the CCND2 gene promoter.

Protein kinase C (PKC)-interacting cousin of thioredoxin (PICOT; also termed glutaredoxin 3 (Grx3; Glrx3)) is a ubiquitous protein that can interact with the embryonic ectoderm development (EED) protein via each of its two C-terminal PICOT/Grx homology domains. Since EED is a Polycomb-Group protein and a core component of the polycomb repressive complex 2 (PRC2), we tested the involvement of PICOT in the regulation of PRC2-mediated H3 lysine 27 trimethylation (H3K27me3), transcription and translation of selected PRC2 target genes. A fraction of the cellular PICOT protein was found in the nuclei of leukemia cell lines, where it was associated with the chromatin. In addition, PICOT coimmunoprecipitated with chromatin-residing EED derived from Jurkat and COS-7 cell nuclei. PICOT knockdown led to a reduced H3K27me3 mark and a decrease in EED and EZH2 at the CCND2 gene promoter. In agreement, PICOT-deficient T cells exhibited a significant increase in CCND2 mRNA and protein expression. Since elevated expression levels of PICOT were reported in several different tumors and correlated in the current studies with decreased transcription and translation of the CCND2 gene, we tested whether this opposite correlation exists in human cancers. Data from the Cancer Genome Atlas (TCGA) database indicated statistically significant negative correlation between PICOT and CCND2 in eight different human tumors where the highest correlation was in lung (p = 8.67E-10) and pancreatic (p = 1.06E-5) adenocarcinoma. Furthermore, high expression of PICOT and low expression of CCND2 correlated with poor patient survival in five different types of human tumors. The results suggest that PICOT binding to chromatin-associated EED modulates the H3K27me3 level at the CCND2 gene promoter which may be one of the potential mechanisms for regulation of cyclin D2 expression in tumors. These findings also indicate that a low PICOT/CCND2 expression ratio might serve as a good predictor of patient survival in selected human cancers.