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Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)—Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine.Implications:This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.

S1. Characteristics of MYC signatures. S2. MYC activity scores capture MYC pathway activity. S3. Diverse mechanisms of MYC alterations captured by MYC activity scores. S4. Prognostic relevance of MYC score. S5. High MYC activity is associated with high proliferative rate of tumor cells.

Figure S1. LIS reflects immune cell infiltration in melanoma microenvironment. Figure S2. LIS is associated with clinical factors and provided prognostic value in addition to clinical information in melanoma. Figure S3. LIS is predictive of prognosis and immunotherapy response and correlated with genomic features in melanoma.

Table S1. Summary of the datasets Table S2. Immune related genes' correlation with ImmuneScore Table S3. 25 genes PC1 loading coefficient Table S4. Primary tumor mutation's association with LIS Table S5. Metastatic tumor mutation's association with LIS Table S6. Primary tumor CNV's association with LIS Table S7. Metastatic tumor CNV's association with LIS

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant.Implications:By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Chromatin accessibility is essential for transcriptional activation of genomic regions. It is well established that transcription factors (TFs) and histone modifications (HMs) play critical roles in chromatin accessibility regulation. However, there is a lack of studies that quantify these relationships. Here we constructed a two-layer model to predict chromatin accessibility by integrating DNA sequence, TF binding, and HM signals. By applying the model to two human cell lines (GM12878 and HepG2), we found that DNA sequences had limited power for accessibility prediction, while both TF binding and HM signals predicted chromatin accessibility with high accuracy. According to the HM model, HM features determined chromatin accessibility in a cell line shared manner, with the prediction power attributing to five core HM types. Results from the TF model indicated that chromatin accessibility was determined by a subset of informative TFs including both cell line-specific and generic TFs. The combined model of both TF and HM signals did not further improve the prediction accuracy, indicating that they provide redundant information in terms of chromatin accessibility prediction. The TFs and HM models can also distinguish the chromatin accessibility of proximal versus distal transcription start sites with high accuracy. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-08234-5.

c-MYC (MYC) is deregulated in more than 50% of all cancers. While MYC amplification is the most common MYC-deregulating event, many other alterations can increase MYC activity. We thus systematically investigated MYC pathway activity across different tumor types. Using a logistic regression framework, we established tumor type–specific, transcriptomic-based MYC activity scores that can accurately capture MYC activity. We show that MYC activity scores reflect a variety of MYC-regulating mechanisms, including MYCL and/or MYCN amplification, MYC promoter methylation, MYC mRNA expression, lncRNA PVT1 expression, MYC mutations, and viral integrations near the MYC locus. Our MYC activity score incorporates all of these mechanisms, resulting in better prognostic predictions compared with MYC amplification status, MYC promoter methylation, and MYC mRNA expression in several cancer types. In addition, we show that tumor proliferation and immune evasion are likely contributors to this reduction in survival. Finally, we developed a MYC activity signature for liquid tumors in which MYC translocation is commonly observed, suggesting that our approach can be applied to different types of genomic alterations. In conclusion, we developed a MYC activity score that captures MYC pathway activity and is clinically relevant. Implications: By using cancer type–specific MYC activity profiles, we were able to assess MYC activity across many more tumor types than previously investigated. The range of different MYC-related alterations captured by our MYC activity score can be used to facilitate the application of future MYC inhibitors and aid physicians to preselect patients for targeted therapy.

Developing prognostic biomarkers for specific cancer types that accurately predict patient survival is increasingly important in clinical research and practice. Despite the enormous potential of prognostic signatures, proposed models have found limited implementations in routine clinical practice. Herein, we propose a generic, RNA sequencing platform-independent, statistical framework named Whole Transcriptome Signature for Prognostic Prediction (WTSPP) to generate prognostic gene signatures. Using ovarian cancer and lung adenocarcinoma as examples, we provide evidence that our prognostic signatures over-perform previous reported signatures, capture prognostic features not explained by clinical variables and expose biologically relevant prognostic pathways, including those involved in the immune system and cell cycle. Our approach demonstrates a robust method for developing prognostic gene expression signatures. In conclusion, our statistical framework can be generally applied to all cancer types for prognostic prediction and might be extended to other human diseases. The proposed method is implemented as an R package (PanCancerSig) and is freely available on GitHub (https://github.com/Cheng-Lab-GitHub/PanCancer_Signature).

BackgroundMelanoma patients who develop immunotherapy-related adverse events often have durable responses to treatment. We previously identified that long-term melanoma survivors presenting with the autoimmune adverse event, vitiligo, developed long lived CD8+ resident memory T cell (TRM) responses in skin and tumor with circulating memory T cell (TCIRC) clonal counterparts in blood.1 Despite the focus on CD8+ T cells in prior studies, CD4+ T cell features remain largely in the background.MethodsUsing the same patient cohort, we performed parallel single-cell RNA sequencing (scRNAseq) and single-cell TCR sequencing (scTCRseq) on CD4+ T cells sorted from matched skin, tumor, and blood using the 10X Genomics platform. The UMI counts-based gene expression matrix was processed using the R package Seurat (v.3.0).ResultsEleven distinct CD4+ T cell clusters were identified. The FOXP3 expressing regulatory T cell (Treg) cluster was comprised of cells from skin, tumor, and blood, and could be further sub-clustered into 3 distinct populations with one having transcripts associated with Treg activation. Of the T helper-like clusters, we identified subsets with transcripts associated with cytotoxicity (GZMA, GNLY, CX3CR1; TCYTO), exhaustion (PDCD1, HAVCR2, TOX; TEX), and three clusters that were excluded from blood with clear resident memory characteristics (high CD69, low KLF2, S1PR1). These three clusters were differentiated by expression of IL2 (TRM-IL2); ID2 and CD40LG (TRM-ACTIVATED) and CD28 (TRM-CD28). Paired scTCRseq revealed a high level of clonal overlap between the TCYTO and the TRM-ACTIVATED clusters, with RNA velocity analysis supporting a potential differentiation trajectory from TRM-ACTIVATED to TCYTO. Integrating our previously published CD8+ TRM and TCIRC profiles, we identified a core TRM signature and core TCIRC signature from both the CD4+ and CD8+ TRM and TCIRC cells, respectively, in melanoma patients. The core TRM signature predicted better overall survival of advanced melanoma patients in TCGA, while the core TCIRC signature did not.ConclusionsThis study supports the crucial anti-tumor role of TRM in cancer patients and extends this important observation to CD4+ T cells.ReferenceHan JC, Zhao YD, Shirai K, Molodtsov A, Kolling FW, Fisher JL, Zhang PS, Yan SF, Searles TG, Bader JM, Gui J, Cheng C, Ernstoff MS, Turk MJ, Angeles CV. Resident and circulating memory T cells persist for years in melanoma patients with durable responses to immunotherapy. Nature Cancer 2021;2(3).Ethics ApprovalIRB-approved written informed consent was obtained from patients with advanced melanoma, to perform skin and tumor biopsies, draw blood, and to access historical banked tissue and blood samples for analysis. All human studies were performed in accordance with ethical regulation, and pre-approved by the Committee for the Protection of Human Subjects at Dartmouth-Hitchcock Medical Center IRB (#00029821).

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Transcription factor (TF) STAT3 contributes to pancreatic cancer progression through its regulatory roles in both tumor cells and the tumor microenvironment (TME). In this study, we performed a systematic analysis of all TFs in patient-derived gene expression datasets and confirmed STAT3 as a critical regulator in the pancreatic TME. Importantly, we developed a novel framework that is based on TF target gene expression to distinguish between environmental- and tumor-specific STAT3 activities in gene expression studies. Using this framework, our results novelly showed that compartment-specific STAT3 activities, but not STAT3 mRNA, have prognostications towards clinical values within pancreatic cancer datasets. In addition, high TME-derived STAT3 activity correlates with an immunosuppressive TME in pancreatic cancer, characterized by CD4 T cell and monocyte infiltration and high copy number variation burden. Where environmental-STAT3 seemed to play a dominant role at primary pancreatic sites, tumor-specific STAT3 seemed dominant at metastatic sites where its high activity persisted. In conclusion, by combining compartment-specific inference with other tumor characteristics, including copy number variation and immune-related gene expression, we demonstrate our method’s utility as a tool to generate novel hypotheses about TFs in tumor biology.

While T-cell responses to cancer immunotherapy have been avidly studied, long-lived memory has been poorly characterized. In a cohort of metastatic melanoma survivors with exceptional responses to immunotherapy, we probed memory CD8+ T-cell responses across tissues, and across several years. Single-cell RNA sequencing revealed three subsets of resident memory T (TRM) cells shared between tumors and distant vitiligo-affected skin. Paired T-cell receptor sequencing further identified clonotypes in tumors that co-existed as TRM in skin and as effector memory T (TEM) cells in blood. Clonotypes that dispersed throughout tumor, skin and blood preferentially expressed an IFNG/TNF-high signature, which had a strong prognostic value for patients with melanoma. Remarkably, clonotypes from tumors were found in patient skin and blood up to 9 years later, with skin maintaining the most focused tumor-associated clonal repertoire. These studies reveal that cancer survivors can maintain durable memory as functional, broadly distributed TRM and TEM compartments. Turk and colleagues analyze exceptional responders to checkpoint blockade for melanoma, and detect tissue-resident memory and effector memory T-cell clonotypes in skin and blood, respectively, up to 9 years after treatment.

The mechanism controlling the dynamic targeting of SWI/SNF has long been postulated to be coordinated by transcription factors (TFs), yet demonstrating a specific TF influence has proven difficult. Here we take a multi-omics approach to interrogate transient SWI/SNF interactors, chromatin targeting and the resulting three-dimensional epigenetic landscape. We utilize the labeling technique TurboID to map the SWI/SNF interactome and identify the activator protein-1 (AP-1) family members as critical interacting partners for SWI/SNF complexes. CUTRUN profiling demonstrates SWI/SNF targeting enrichment at AP-1 bound loci, as well as SWI/SNF-AP-1 cooperation in chromatin targeting. HiChIP reveals AP-1-SWI/SNF-dependent restructuring of the three-dimensional promoter-enhancer architecture and generation of enhancer hubs. Through interrogation of the SWI/SNF-AP-1 interaction, we demonstrate an SWI/SNF dependency on AP-1-mediated chromatin localization. We propose that pioneer factors, such as AP-1, bind and target SWI/SNF to inactive chromatin, where it restructures the genomic landscape into an active state through epigenetic rewiring spanning multiple dimensions.

The nature of the anti-tumor immune response changes as primary tumors progress and metastasize. We investigated the role of resident memory (Trm) and circulating memory (Tcirm) cells in anti-tumor responses at metastatic locations using a mouse model of melanoma-associated vitiligo. We found that the transcriptional characteristics of tumor-specific CD8+ T cells were defined by the tissue of occupancy. Parabiosis revealed that tumor-specific Trm and Tcirm compartments persisted throughout visceral organs, but Trm cells dominated lymph nodes (LNs). Single cell RNA sequencing profiles of LN Trm and skin Trm cells in LN and skin were distinct, but shared clonotypes that occupied both tissues were preferentially overwhelmingly maintained as Trm in LNs. Whereas Tcirm cells prevented melanoma growth in the lungs, Trm afforded long-lived protection against melanoma seeding in LNs. Expanded Trm populations were also present in melanoma-involved LNs from patients, and their transcriptional signature predicted better survival. Thus tumor-specific Trm cells persist in LNs, restricting metastatic cancer.

EGFR is an oncogene with a high frequency of activating mutations in nonsmall cell lung cancer (NSCLC). EGFR inhibitors have been FDA-approved for NSCLC and have shown efficacy in patients with certain EGFR mutations. However, only 9% to 26% of these patients achieve objective responses. In our study, we developed an EGFR gene signature based on The Cancer Genome Atlas (TCGA) RNA-seq data of lung adenocarcinoma (LUAD) to direct the preselection of patients for more effective EGFR-targeted therapy. This signature infers baseline EGFR signaling pathway activity (denoted as EGFR score) in tumor samples, which is associated with tumor sensitivity to EGFR inhibitors and other tyrosine kinase inhibitors (TKIs). EGFR score predicted sensitivity of lung cancer cell lines to Erlotinib, Gefitinib and Sorafenib. Importantly, EGFR score calculated from pretreated samples was associated with patient response to Gefitinib and Sorafenib in lung cancer. Additionally, integration of the EGFR signature with TCGA LUAD data showed that it accurately predicted functional effects of different somatic EGFR mutations, and identified other mutations affecting EGFR pathway activity. Finally, using cancer cell line and clinical trial data, the EGFR score was associated with patient response to TKIs in liver cancer and other cancer types. The EGFR signature provides a useful biomarker that can expand the application of EGFR inhibitors or other TKIs and improve their treatment efficacy through patient stratification.

Huntington’s disease is caused by the pathological expansion of a polyglutamine (polyQ) stretch in Huntingtin (Htt), but the molecular mechanisms by which polyQ expansion in Htt causes toxicity in selective neuronal populations remain poorly understood. Interestingly, heterologous expression of expanded polyQ Htt is toxic in Saccharomyces cerevisiae cells, but has no effect in Schizosaccharomyces pombe, a related yeast species possessing very few endogenous polyQ or Q/N-rich proteins. Here, we used a comprehensive and unbiased mass spectrometric approach to identify proteins that bind Htt in a length-dependent manner in both species. Analysis of the expanded polyQ-associated proteins reveals marked enrichment of proteins that are localized to and play functional roles in nucleoli and mitochondria in S. cerevisiae, but not in S. pombe. Moreover, expanded polyQ Htt appears to interact preferentially with endogenous polyQ and Q/N-rich proteins, which are rare in S. pombe, as well as proteins containing coiled-coil motifs in S. cerevisiae. Taken together, these results suggest that polyQ expansion of Htt may cause cellular toxicity in S. cerevisiae by sequestering endogenous polyQ and Q/N-rich proteins, particularly within nucleoli and mitochondria.

Summary The nature of the anti-tumor immune response changes as primary tumors progress and metastasize. We investigated the role of resident memory (Trm) and circulating memory (Tcirm) cells in anti-tumor responses at metastatic locations using a mouse model of melanoma-associated vitiligo. We found that the transcriptional characteristics of tumor-specific CD8+ T cells were defined by the tissue of occupancy. Parabiosis revealed that tumor-specific Trm and Tcirm compartments persisted throughout visceral organs, but Trm cells dominated lymph nodes (LNs). Single-cell RNA-sequencing profiles of Trm cells in LN and skin were distinct, and T cell clonotypes that occupied both tissues were overwhelmingly maintained as Trm in LNs. Whereas Tcirm cells prevented melanoma growth in the lungs, Trm afforded long-lived protection against melanoma seeding in LNs. Expanded Trm populations were also present in melanoma-involved LNs from patients, and their transcriptional signature predicted better survival. Thus, tumor-specific Trm cells persist in LNs, restricting metastatic cancer.

A VISTA on naïve T cell fate T cell quiescence and tolerance restrain the immune system from becoming overactive and attacking healthy tissue. Negative checkpoint regulators normally limit T cell responses to help safeguard against conditions such as autoimmunity. ElTanbouly et al. report that the checkpoint regulator VISTA (V-type immunoglobulin domain-containing suppressor of T cell activation) restricts early stages of T cell activation by shaping the inherent heterogeneity of the naïve CD4 + T cell compartment to one that is more uniformly quiescent and silent (see the Perspective by Brown and Rudensky). Therapeutic targeting of VISTA using an agonistic antibody in mice curbed the development of graft-versus-host disease and promoted the death of naïve T cells abnormally activated by self-antigen. VISTA thus represents a distinctive immunoregulatory molecule that controls naïve T cell function by maintaining quiescence and peripheral tolerance. Science , this issue p. eaay0524 ; see also p. 247

Background Neuroblastoma (NB) is a heterogeneous disease with respect to genomic abnormalities and clinical behaviors. Despite recent advances in our understanding of the association between the genetic aberrations and clinical features, it remains one of the major challenges to predict prognosis and stratify patients for determining personalized therapy in this disease. The aim of this study was to develop an effective prognosis prediction model for NB patients. Methods We integrated diverse computational analyses to define gene signatures that reflect MYCN activity and chromosomal aberrations including deletion of chromosome 1p (Chr1p_del) and chromosome 11q (Chr11q_del) as well as chromosome 11q whole loss (Chr11q_wls). We evaluated the prognostic and predictive values of these signatures in seven NB gene expression datasets (the number of samples ranges from 94 to 498, with a total of 2120) generated from both RNA sequencing and microarray platforms. Results MYCN signature was a more effective prognostic marker than MYCN amplification status and MYCN expression. Similarly, the Chr1p_del score was more prognostic than Chr1p status. The activity scores of MYCN, Chr1p_del and Chr11q_del were associated with poor prognosis, while the Chr11q_wls score was linked to good outcome. We integrated the activity scores of MYCN, Chr1p_del, Chr11q_del, and Chr11q_wls and clinical variables into an integrative prognostic model, which displayed significant performance over the clinical variables or each genomic aberration alone. Conclusions Our integrative gene signature model shows a significantly improved forecast performance with prognostic and predictive information, and thereby can be served as a biomarker to stratify NB patients for prognosis evaluation and surveillance programs.

While immune responses against primary tumors are critically important, T cells must also be capable of functioning at sites where cancers metastasize. Here we investigated how resident memory (TRM) and circulating memory (TCIRCM) CD8 T cells potentiate immunity to cancer in diverse tissue microenvironments. Based on a mouse model of immunity to melanoma with associated autoimmune vitiligo, we show that tumor-specific memory T cells are capable of forming a widespread network of transcriptionally distinct subsets, throughout lymphoid tissues and visceral organs. Among these, we discovered a population of TRM cells that reside durably within LNs, where they protect against invading melanoma cells. These LN-resident memory (LN TRM) cells adopt a transcriptional program that is distinct from TRM cells in other tissues, and which uniquely predicts survival in melanoma patients with regional LN metastases. This work reveals a novel role for TRM cells in durable immunity to cancer at crucial sites of metastasis.

Background Neuroblastoma (NB) is the most common extracranial solid tumor found in children. The frequent gain/loss of many chromosome bands in tumor cells and absence of mutations found at diagnosis suggests that NB is a copy number-driven cancer. Despite the previous work, a systematic analysis that investigates the relationship between such frequent gain/loss of chromosome bands and patient prognosis has yet to be implemented. Methods First, we analyzed two NB CNV datasets to select chromosomal bands with a high frequency of gain or loss. Second, we applied a computational approach to infer sample-specific CNVs for each chromosomal band selected in step 1 based on gene expression data. Third, we applied univariate Cox proportional hazards models to examine the association between the resulting inferred copy number values (iCNVs) and patient survival. Finally, we applied multivariate Cox proportional hazards models to select chromosomal bands that remained significantly associated with prognosis after adjusting for critical clinical variables, including age, stage, gender, and MYCN amplification status. Results Here, we used a computational method to infer the copy number variations (CNVs) of sample-specific chromosome bands from NB patient gene expression profiles. The resulting inferred CNVs (iCNVs) were highly correlated with the experimentally determined CNVs, demonstrating CNVs can be accurately inferred from gene expression profiles. Using this iCNV metric, we identified 58 frequent gain/loss chromosome bands that were significantly associated with patient survival. Furthermore, we found that 7 chromosome bands were still significantly associated with patient survival even when clinical factors, such as MYCN status, were considered. Particularly, we found that the chromosome band chr11p14 has high potential as a novel candidate cytogenetic biomarker for clinical use. Conclusion Our analysis resulted in a comprehensive list of prognostic chromosome bands supported by strong statistical evidence. In particular, the chr11p14 gain event provided additional prognostic value in addition to well-established clinical factors, including MYCN status, and thereby represents a novel candidate cytogenetic biomarker with high clinical potential. Additionally, this computational framework could be readily extended to other cancer types, such as leukemia.

Additional file 9: Figure S1. The landscape of chromosome bands gain/loss on Kocak dataset. Figure S2. The landscape of chromosome bands gain/loss on Pugh dataset.

Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)—Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine. Implications: This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis.

In eukaryotes, DNA replication initiates from multiple origins of replication for timely genome duplication. These sites are selected by origin licensing, during which the core enzyme of the eukaryotic DNA replicative helicase, the Mcm2-7 (minichromosome maintenance) complex, is loaded at each origin. This origin licensing requires loading two Mcm2-7 helicases around origin DNA in a head-to-head orientation. Current models suggest that the origin-recognition complex (ORC) and cell-division cycle 6 (Cdc6) proteins recognize and encircle origin DNA and assemble an Mcm2-7 double-hexamer around adjacent double-stranded DNA. To test this model and assess the location of Mcm2-7 initial loading, we placed DNA-protein roadblocks at defined positions adjacent to the essential ORC-binding site within Saccharomyces cerevisiae origin DNA. Roadblocks were made either by covalent cross-linking of the HpaII methyltransferase to DNA or through binding of a transcription activator-like effector (TALE) protein. Contrary to the sites of Mcm2-7 recruitment being precisely defined, only single roadblocks that inhibited ORC-DNA binding showed helicase loading defects. We observed inhibition of helicase loading without inhibition of ORC-DNA binding only when roadblocks were placed on both sides of the origin to restrict sliding of a helicase-loading intermediate. Consistent with a sliding helicase-loading intermediate, when either one of the flanking roadblocks was eliminated, the remaining roadblock had no effect on helicase loading. Interestingly, either origin-flanking nucleosomes or roadblocks resulted in helicase loading being dependent on an additional origin sequence known to be a weaker ORC-DNA-binding site. Together, our findings support a model in which sliding helicase-loading intermediates increase the flexibility of the DNA sequence requirements for origin licensing., American Cancer Society. Postdoctoral Fellowship (123700-PF-13-071-01-DMC), National Institutes of Health (U.S.). Pre-Doctoral Training Program (Grant GM007287), National Science Foundation (U.S.). Graduate Research Fellowship (1122374), National Cancer Institute (U.S.) (Grant P30-CA14051)

Background: Lung cancer is associated with the highest mortality rate of all cancer types, and the most common histologic subtype of lung cancer is adenocarcinoma. To apply more effective therapeutic treatment, molecular markers that are able to predict the recurrence risk of patients with adenocarcinoma are critically needed. Mutations in TP53 tumor suppressor gene have been found in approximately 50% of lung adenocarcinoma cases, but the presence of a TP53 mutation does not always associate with increased mortality. Methods: The Cancer Genome Atlas RNA sequencing data of lung adenocarcinoma were used to define a novel gene signature for P53 deficiency. This signature was then used to calculate a sample-specific P53 deficiency score based on a patient's transcriptomic profile and tested in four independent lung adenocarcinoma microarray datasets. Results: In all datasets, P53 deficiency score was a significant predictor for recurrence-free survival where high P53 deficiency score was associated with poor survival. The score was prognostic even after adjusting for several key clinical variables including age, tumor stage, smoking status, and P53 mutation status. Furthermore, the score was able to predict recurrence-free survival in patients with stage I adenocarcinoma and was also associated with smoking status. Conclusions: The P53 deficiency score was a better predictor of recurrence-free survival compared with P53 mutation status and provided additional prognostic values to established clinical factors. Impact: The P53 deficiency score can be used to stratify early-stage patients into subgroups based on their risk of recurrence for aiding physicians to decide personalized therapeutic treatment. Cancer Epidemiol Biomarkers Prev; 27(1); 86–95. ©2017 AACR.

A novel 20% concentration cross-linked agarose beads was prepared and successfully applied in the separation and purification of resveratrol and polydatin from crude root extracts of Polygonum cuspidatum. The optimal separation conditions were carried out with 20% acetic acid and 20% ethanol mixed solution (V/V) at a flow rate of 1.0 mL/min and a sample load of 16 mg crude extract (corresponding to a load of 1.0 mg/mL beads). The purities of the collected resveratrol and polydatin were more than 98.0% and the corresponding yields were 93.3% and 92.6%, respectively. The obtained 20% agarose beads were high chemical stability and load capacity, a low column back pressure, which could provide an alternative method for the separation and purification of active polyphenols that are frequently found in medicinal plants.

Tissue resident memory T cells (TRM cells) have recently been recognized as durable mediators of immunity to cancer. We previously showed that regulatory T cell-depleting immunotherapy of B16 melanoma induces protective TRM cells that persist in the skin of mice that develop autoimmune vitiligo. The goal of the present study was to assess the host-wide diversity and function of memory CD8 T cells throughout peripheral tissues of these mice. Using Pmel transgenic CD8 T cells to track Ag-specific responses revealed the generation of memory T cells with a TRM-like phenotype (CD44hi CD62Llow CD103+CD69+) throughout skin, lungs and liver. Parabiotic transfer/equilibration experiments demonstrated the presence of TRM cells in each peripheral tissue and also, surprisingly, in tumor-draining lymph nodes. Tumor protection experiments in parabiotic mice, and after treatment with the S1PR antagonist FTY720, indicated roles for both TRM cells and circulating memory T cells in providing long-lived protection against melanoma re-challenge at various tissue locations. Single-cell transcriptional profiling of memory CD8 T cells isolated from the skin, lungs, liver, lymph nodes, and spleen indicated the presence of diverse populations with features of both circulating and resident memory, but with TRM cell populations dominating in peripheral tissues and tumor-draining lymph nodes. Moreover, clonally-identical TRM cells in the skin, liver, lungs, and lymph nodes each possessed unique transcriptional features exclusive to their tissue of origin. These studies highlight the tissue-specific adaptations of tumor-reactive TRM cells, and the importance of host-wide TRM responses in providing immunity to cancer.

The preparation of Zn(II)-immobilized glutaraldehyde-crosslinked chitosan microspheres which was modified with epichlorohydrin, tetraethylenepentamine, and bromoacetic acid was presented in this work. The Zn(II)-immobilized value of the microspheres (Ac-TEPA-CS) is 43.6 mg g−1, which is higher than the blank microspheres. The adsorption of urea onto Zn-Ac-TEPA-CS was studied in a batch system. Langmuir and Freundlich adsorption models were applied to describe the experimental isotherm and isotherm constant, and the kinetic of adsorption process were estimated. These data fits well with Langmuir isotherm and also indicated that the adsorption process is exothermic and follow the pseudo-second-order kinetics. The adsorption capacity depends upon the pH, the temperature and the initial concentration of urea. It observed that Zn-Ac-TEPA-CS could be repeatedly used by elution and regeneration without significant loss of adsorption capacity.

Supermacroporous agarose/chitosan composite monolithic (AC CM) cryogels were prepared for affinity purification of the major egg white glycoproteins, ovalbumin (OVA), and ovotransferrin (OVT). The supermacroporous AC CM cryogels were produced by cryocopolymerization of agarose/chitosan blend solutions using glutaraldehyde as the cross-linker. The 3-aminophenlyboronic acid ligand was immobilized by covalent binding to epoxy-group-coupled supermacroporous AC CM cryogels. The microstructure morphologies of these cryogels were analyzed by scanning electron microscopy. The supermacroporous AC CM cryogels contained a continuous interpenetrating polymer network matrix with interconnected pores of 10–100 μm in size. The composite cryogels offered high mechanical stability and had specific recognition for glycoproteins. The maximum binding capacity of OVA adsorption from aqueous solutions was 55.6 mg/g. The matrix could be reused 11 times without significant loss in OVA adsorption capacity. The recovery yields of OVA and OVT from egg white were estimated to be 89 and 93%, respectively.

Supermacroporous agarose/chitosan composite monolithic (AC CM) cryogels were prepared for affinity purification of the major egg white glycoproteins, ovalbumin (OVA), and ovotransferrin (OVT). The supermacroporous AC CM cryogels were produced by cryocopolymerization of agarose/chitosan blend solutions using glutaraldehyde as the cross-linker. The 3-aminophenlyboronic acid ligand was immobilized by covalent binding to epoxy-group-coupled supermacroporous AC CM cryogels. The microstructure morphologies of these cryogels were analyzed by scanning electron microscopy. The supermacroporous AC CM cryogels contained a continuous interpenetrating polymer network matrix with interconnected pores of 10-100 μm in size. The composite cryogels offered high mechanical stability and had specific recognition for glycoproteins. The maximum binding capacity of OVA adsorption from aqueous solutions was 55.6 mg/g. The matrix could be reused 11 times without significant loss in OVA adsorption capacity. The recovery yields of OVA and OVT from egg white were estimated to be 89 and 93%, respectively.

In order to obtain a novel absorbent with high adsorption capacity for the purification of immunoglobulin G (IgG), continuous supermacroporous agarose beads embedded agarose-chitosan composite monolithic cryogels (agarose-chitosan cryogels) were prepared by cryo-copolymerization of agarose-chitosan blend solutions with glutaraldehyde as the crosslinker in the presence of agarose beads. After coupling 2-mercaptopyridine onto divinylsulfone-activated matrix, the obtained cryogels were used for the purification of IgG. The microstructure morphologies of the cryogels were analyzed by scanning electron microscopy. The results showed that the obtained cryogels possess interconnected pores of 10-100 μm size. The specific surface area was 350 m(2)/g with maximum adsorption capacity of IgG 71.4 mg/g. The cryogels showed workable stability, and can be reused at least 15 times without significant loss in adsorption capacity. IgG purity after one-step purification from human plasma was monitored by electrophoresis and the average recovery was estimated to be 90%.