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  • 1
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 1441-1441
    Abstract: Nivolumab, a PD-1 inhibitor, has variable response rates in patients and is not fully characterized in treatment-naïve patients. Here, we describe exploratory analyses of immune-related gene expression in squamous cell carcinoma of the head and neck (SCCHN) as predictors of response to nivolumab, administered for 4 weeks before planned surgical resection in the context of a window-of-opportunity trial. RNA-seq was performed on pre- and post-treatment tumor tissues from 39 patients with SCCHN of any stage, who were candidates for complete surgical resection (NCT03238365). Expression was quantified using kallisto. Noncoding, histone-coding and mitochondrial transcripts were removed. HPV-specific reads were filtered using pathseq and aligned to HPV reference using viGEN. TME signature scores were quantified using ssGSEA. While HPV-status did not predict clinical responses to nivolumab, the expression of individual HPV16 genes in post-treatment samples reflected response in this patient cohort. Patients who responded to nivolumab showed lower levels of E6 expression, while non-responsive patients had significantly higher E6 expression levels. In contrast, E4 expression was found to be increased in patients who responded to nivolumab treatment. As expected, HPV-positive tumors presented with a more inflamed TME compared to HPV-negative tumors. A tumor microenvironment (TME) classification platform developed by BostonGene was used to analyze several gene expression signatures. Four distinct microenvironment subtypes were reproduced, consistent with pooled analysis. In addition, a high proliferation rate signature in baseline samples was closely associated with non-response to immunotherapy regardless of HPV status. HPV-negative tumors with significantly higher CD8, FoxP3, and CD163 as measured by IHC, had a greater response to immunotherapy in contrast to HPV-positive tumors, where no association was found. This finding was supported by single gene expression and the BostonGene-developed deconvolution algorithm to reconstruct the TME composition of the tumors using RNA sequencing; predicted CD8+ T-cells and Macrophages were significantly enriched in HPV-negative responders. Interestingly, patients with HPV-negative tumors disproportionately responded better to treatment when they presented with an immune-inflamed TME; however, this pattern was not observed in HPV-positive tumors. Our analysis indicates that HPV16 gene transcription appears to impact response to treatment. In addition, the immune-inflamed TME impacts response to nivolumab treatment in HPV-negative tumors. These properties can be assessed in a multiparametric analysis and could lead to the identification of predictors of response to immunotherapy in head and neck cancer. Citation Format: Nikita Kotlov, Zoya Antysheva, Dina Antonova, Naira Samarina, Sandrine Degryse, Alban Linnenbach, Sanket Shukla, Larry Harshyne, Andrew P. South, Jennifer M. Johnson, Young Kim, Alexander Bagaev, Nathan H. Fowler, Adam Luginbuhl. Predictors of treatment response in a preoperative window of opportunity trial of nivolumab in resectable squamous cell carcinoma of the head and neck [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1441.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 3182-3182
    Abstract: Gastric Cancer (GC) is the second leading cause of cancer-related mortality (9.7% of the total) and most patients with advanced disease will die within one year of diagnosis. GC is histologically classified into intestinal, diffuse and the mixed types, and into four molecular subtypes based on genetic profiling (i.e. microsatellite instable (MSI), EBV positive, chromosomal instable, and genomically stable). Although the molecular annotation is meaningful, the tumor immune microenvironment (TIME) has largely not been evaluated. Using an integrated collection of 11 public cohorts (n=2,270), we identified 5 unique GC TIME phenotypes by unsupervised clustering of gene expression signatures of RNA that describe the composition and biology of TIME and properties of malignant cells: two stromal-enriched subtypes - 1) Mesenchymal-wnt activated, high stroma activation and WNT signaling and 2) Fibrotic, only high stroma activation; two immune enriched subtypes 3) Inflamed non-fibrotic, high immune infiltration and low stromal compartment and 4) B-cell inflamed, high B cell activation; and 5) Immune Depleted, lowest immune and the highest malignant cell properties. The clusters were robust, being identified across all 11 datasets and across all stages of disease. Intestinal, diffuse, and mixed histologies were identified in each cluster. These clusters will be orthogonally validated using immunohistochemistry. The current molecular subtypes were represented in each of our TIME clusters, with some enrichment. Specifically, we found enrichment of MSI molecular subtype, characterized by hypermutation and microsatellite instability, in “Inflamed, non-fibrotic” cluster whereas the MSS/EMT subtype, associated with poor overall survival, was enriched in “Mesenchymal, wnt activated” cluster. We also saw specific enrichment of EBV positive tumors, known to have good prognosis, in both immune-enriched clusters. These results show a high concordance with the current TCGA/ACRG molecular subtypes of GC. These TIME clusters are prognostic in GC. The “Inflamed, non-fibrotic” cluster demonstrated a better overall and relapse free survival whereas stromal enriched clusters exhibited the worst (p & lt;0.001, HR=2.27). Interestingly, the most aggressive “Mesenchymal, wnt activated” subtype was also enriched of metastatic samples. These results were confirmed using an independent validation cohort (n=231) from four other datasets. Additionally, comparison of matching on-treatment vs baseline biopsies from 7 patients treated with cabazitaxel further suggested that TIME changed upon treatment and, in some cases, was indicative of poor response to taxanes. We have defined and characterized the TIME for GC. The GC microenvironment is both prognostic for patient outcome and predictive of response to cytotoxic therapy. Citation Format: Prashant V. Thakkar, Olga Kudryashova, Daria Melikhova, Naira Samarina, Sandrine Degryse, Alexander Bagaev, Felix Frenkel, Svetlana Podsvirova, Dmitry Tychinin, Sandipto Sarkar, Rhonda K. Yantiss, Nathan Fowler, Manish A. Shah. Tumor immune microenvironment based molecular functional clustering reveals a prognostic signature that predicts overall survival in patients with gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3182.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
    RVK:
    RVK:
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2021
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 5405-5405
    Abstract: The ability to locate a tumor primary site for patients with a cancer of unknown primary (CUP) is a major obstacle in providing personalized therapeutic options and access to clinical trials. Despite the recent use of molecular-based tools to identify the tumor tissue-of-origin (TOO), overall survival for CUP patients remains low. Here, we present an AI-based tool that predicts the TOO by using genomic and transcriptomic data to classify CUP tumors into hierarchically-organized molecular subgroups. The TOO predictor was composed of DNA, RNA, and Consensus classifiers that were hierarchically organized with respect to molecular diagnosis with upper level clusters based on common molecular features reflecting similar cell of origin, and lower levels containing specific diagnoses for further classification. The ML-based DNA classifier was trained on a dataset of publicly available genomic data generated from 8,000 samples, and independently validated using more than 5,500 samples. The ML-based RNA classifier was trained on a dataset of publicly available transcriptomic data created from more than 10,100 samples with tumor- and normal-specific features for each cancer type, and independently validated using 20,000 samples. The Consensus classifier, combining outputs from both DNA and RNA algorithms, was trained on a dataset of genomic and transcriptomic data from 1,000 samples, and validated on an independent dataset of 2,000 samples. Each classifier contained features selected based on data analysis according to the weighted F1-score, and the best hyperparameters for the final model. The 3-classifier algorithm predicts TOO for 33 cancer types and subtypes belonging to solid neoplasms, independently of sample source, sequencing methods, and cohort. Validation of the Consensus classifier showed a higher accuracy (95% f1-score) compared to the DNA and RNA classifiers (79% and 93% f1-scores, respectively), along with a high sensitivity (95%), specificity (99%), and precision (96%), as it takes into account both genomic events and expression patterns. The TOO predictor was prospectively validated on approximately 298 clinical samples with a known diagnosis using all classifiers. The diagnosis was identified in 90% of clinical cases (295/297) by the Consensus classifier with 90% sensitivity and 94% precision. The call rate for the DNA and RNA classifiers was above 95%. Of note, sensitivity of the top 4 predicted diagnoses was & gt; 90% for all 3 classifiers, and the calculated rule-out accuracy of the Consensus classifier was 97%. In conclusion, an ML-based algorithm was developed that utilizes genomic and transcriptomic data to accurately predict the TOO for CUP tumors. Utilizing the Consensus classifier after DNA and RNA classifiers helps to identify the TOO of the tumor with high specificity, which can guide precision oncology therapeutic options. Citation Format: Zoia Antysheva, Daria Kiriy, Anton Sivkov, Alexander Sarachackov, Alexandra Boyko, Naira Samarina, Nara Shin, Jessica H. Brown, Ivan Kozlov, Viktor Svekolkin, Alexander Bagaev, Nathan Fowler, Nikita Kotlov. An ML-based tool for predicting tissue of origin for cancer of unknown primary (CUP) based on genomic and transcriptomic data. [abstract] . In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5405.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 4
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 83, No. 7_Supplement ( 2023-04-04), p. 2143-2143
    Abstract: CUP is a relatively common diagnosis that accounts for 3-9% of all cancers. The prognosis is poor with median survival of approximately 9 months. The identification of the primary tumor and therapy targets could improve the survival of these patients. We employed the BostonGene Tumor PortraitTM platform to interrogate 19 CUP cases. Trained on & gt;19,000 samples and validated on 28,000 samples from independent datasets, the machine-learning based algorithm integrates whole-exome and RNA sequencing (WES and RNAseq) analysis to characterize cancer drivers, the tumor microenvironment, potential targets, tumor composition, molecular signatures, and site of origin (94% sensitivity and 99% specificity). The predicted tissue of origin was considered acceptable when it was compatible with tumor histopathology and immunoprofile, and included in the differential diagnosis of radiologic studies. The discovered biomarkers and possible treatments were discussed during our multidisciplinary precision oncology meeting. 16 out of 19 CUP cases (84%) had an acceptable predicted tissue of origin. Two cases lacked clinical evidence to support the predicted primary tumor, and 1 case failed RNAseq. Lung accounted for most of the sites of origin (31%) followed by gastrointestinal (15%) and breast cancers (8%). Other diagnoses included melanoma, uterine, bladder, and renal carcinomas, among others. Except for one case, a clinically significant biomarker or target was found. Those included relevant mutational signatures (e.g., homologous recombination deficiency, DNA mismatch repair), genetic characteristics (high tumor mutational burden (TMB), microsatellite instability), activating alterations (FGFR1, MYC, ERBB2 amplifications; NCOA4::RET fusion), loss of function in tumor suppressor genes (TP53, FANCA, ATM), and gene overexpression (ER). Further, microenvironment analysis characterized the tumor immune infiltrate and the level of RNA expression of PD-L1, PD-L2, and CTLA4. These oncology biomarkers and potential targets are of significant value independent of tissue of origin. In addition, mutations in NF1, KRAS, TP53, MSH2, BRCA1, and PTEN were found and validated by commercially available targeted NGS panels. Based on CUP tumor profiling by this platform, positive treatment response has been observed in 3 out of 4 CUP patients thus far, e.g., one patient with metastatic disease that showed high TMB and immune infiltrated microenvironment treated with Ipilimumab and Nivolumab had a sustained response. Therapy in oncology is often determined by the tissue origin, making CUP a therapeutic challenge. In this study, we demonstrate the application of an integrative WES and RNAseq platform to not only predict the site of origin, but also to identify relevant biomarkers and therapeutic targets in CUP. Citation Format: Majd Al Assaad, Michael Sigouros, Jyothi Manohar, Daniela Guevara, Zoia Antysheva, Daria Kiriy, Alexandra Boyko, Naira Samarina, Nara Shin, Viktor Svekolkin, Svetlana Podsvirova, Noel English, Alaina Villarreal, Brianna McKenna, Cagdas Tazearslan, Diana Shamsutdinova, Vladimir Kushnarev, Troy Kane, David Wilkes, Manish Shah, Barbara Ma, Scott T. Tagawa, David Nanus, Jones Nauseef, Olivier Elemento, Juan Miguel Mosquera, Cora N. Sternberg. Cancer of unknown Primary (CUP): Beyond the identification of the site of origin by an integrative genomic approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2143.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2023
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  • 5
    In: Frontiers in Oncology, Frontiers Media SA, Vol. 12 ( 2022-10-31)
    Abstract: Although immune checkpoint inhibitors (ICIs) are increasingly used as second-line treatments for urothelial cancer (UC), only a small proportion of patients respond. Therefore, understanding the mechanisms of response to ICIs is critical to improve clinical outcomes for UC patients. The tumor microenvironment (TME) is recognized as a key player in tumor progression and the response to certain anti-cancer treatments. This study aims to investigate the mechanism of response using integrated genomic and transcriptomic profiling of a UC patient who was part of the KEYNOTE-045 trial and showed an exceptional response to pembrolizumab. Diagnosed in 2014 and receiving first-line chemotherapy without success, the patient took part in the KEYNOTE-045 trial for 2 years. She showed dramatic improvement and has now been free of disease for over 6 years. Recently described by Bagaev et al., the Molecular Functional (MF) Portrait was utilized to dissect genomic and transcriptomic features of the patient’s tumor and TME. The patient’s tumor was characterized as Immune Desert, which is suggestive of a non-inflamed microenvironment. Integrated whole-exome sequencing (WES) and RNA sequencing (RNA-seq) analysis identified an ATM mutation and high TMB level (33.9 mut/mb), which are both positive biomarkers for ICI response. Analysis further revealed the presence of the APOBEC complex, indicating the potential for use of APOBEC signatures as predictive biomarkers for immunotherapy response. Overall, comprehensive characterization of the patient’s tumor and TME with the MF Portrait revealed important insights that could potentially be hypothesis generating to identify clinically useful biomarkers and improve treatment for UC patients.
    Type of Medium: Online Resource
    ISSN: 2234-943X
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2649216-7
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 3823-3823
    Abstract: Human papillomavirus (HPV)-associated Head and Neck Squamous Cell Carcinoma (HPV+HNSCC) is now the most common HPV-associated malignancy in the United States. Current treatments can be associated with severe side-effects or lack of efficacy yet prognostic biomarkers are limited, slowing efforts to personalize treatment in HPV+HNSCC. Here, we describe the use of a transcriptomic-based analytical platform to analyze expression patterns of viral transcripts, the tumor microenvironment (TME), and viral genome integration, and associate these features with overall survival. Functional gene expression signatures were analyzed on publicly available HPV+HNSCC expression data (n=266). Unsupervised clustering analysis revealed 5 distinct and novel TME types across patients (immune-enriched non-fibrotic, immune-enriched fibrotic, fibrotic, immune-desert, immune-enriched luminal). These microenvironment subtypes were highly correlated with both overall survival and patient prognosis. Tumors with an immune-enriched microenvironment showed the highest survival rates, whereas fibrotic TME types were associated with poor survival (p & lt; 0.05). Unsupervised clustering of a HPV+HNSCC cohort from The Cancer Genome Atlas (TCGA) (n=53), based on HPV transcript expression, revealed 4 HPV-related subtypes. Each subtype was enriched for distinct viral transcripts: E2/E5, E6/E7, E1/E4 and L1/L2. We then validated TME and HPV transcript-related classifications on an independent HPV+HNSCC cohort (n=132). Utilizing both viral transcript and TME subtypes, we found that the E2/E5 HPV subtype was associated with an immune-enriched TME and had a higher overall survival compared to the other subtypes. The E2/E5 subtype was also enriched for samples without HPV-genome integration, suggesting that HPV episomal DNA status and E2/E5 expression pattern may drive an inflamed microenvironment and improved prognosis. In contrast, E6/E7 subtype samples were associated with the fibrotic and depleted TME types, with lower values of T-cell and B-cell gene expression signatures and a lower survival rate. Both E1/E4 and L1/L2 subtypes were associated with the immune-enriched luminal TME types. These findings suggest that HPV-transcript expression patterns may drive modulation of the TME, and hence impact prognosis. Further validation of the relationships between viral gene expression, TME, and prognosis is warranted to understand if such subtypes could aid in the development of prognostic biomarkers for treatment selection. Citation Format: Daria Kiriy, Dmitry Tychinin, Nikita Kotlov, Olga Kudryashova, Anastasia Nikitina, Andrey Tyshevich, Naira Samarina, Ksenia Demina, Sandrine Degryse, Susan Raju Paul, Mark Poznansky, Krystle Lang Kuhs, James S. Lewis, Robert L. Ferris, Xiaowei Wang, Alexander Bagaev, Nathan Fowler, Lori Wirth, Daniel Faden. Viral transcript and tumor immune microenvironment-based transcriptomic profiling of HPV-associated head and neck cancer identifies subtypes associated with prognosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3823.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 7
  • 8
    In: PLOS Pathogens, Public Library of Science (PLoS), Vol. 17, No. 6 ( 2021-6-18), p. e1009635-
    Abstract: Kaposi Sarcoma-associated herpesvirus (KSHV) causes three human malignancies, Kaposi Sarcoma (KS), Primary Effusion Lymphoma (PEL) and the plasma cell variant of multicentric Castleman’s Disease (MCD), as well as an inflammatory cytokine syndrome (KICS). Its non-structural membrane protein, pK15, is among a limited set of viral proteins expressed in KSHV-infected KS tumor cells. Following its phosphorylation by Src family tyrosine kinases, pK15 recruits phospholipase C gamma 1 (PLCγ1) to activate downstream signaling cascades such as the MEK/ERK, NFkB and PI3K pathway, and thereby contributes to the increased proliferation and migration as well as the spindle cell morphology of KSHV-infected endothelial cells. Here, we show that a phosphorylated Y 481 EEVL motif in pK15 preferentially binds into the PLCγ1 C-terminal SH2 domain (cSH2), which is involved in conformational changes occurring during the activation of PLCγ1 by receptor tyrosine kinases. We determined the crystal structure of a pK15 12mer peptide containing the phosphorylated pK15 Y 481 EEVL motif in complex with a shortened PLCγ1 tandem SH2 (tSH2) domain. This structure demonstrates that the pK15 peptide binds to the PLCγ1 cSH2 domain in a position that is normally occupied by the linker region connecting the PLCγ1 cSH2 and SH3 domains. We also show that longer pK15 peptides containing the phosphorylated pK15 Y 481 EEVL motif can increase the Src-mediated phosphorylation of the PLCγ1 tSH2 region in vitro . This pK15-induced increase in Src-mediated phosphorylation of PLCγ1 can be inhibited with the small pK15-derived peptide which occupies the PLCγ1 cSH2 domain. Our findings thus suggest that pK15 may act as a scaffold protein to promote PLCγ1 activation in a manner similar to the cellular scaffold protein SLP-76, which has been shown to promote PLCγ1 activation in the context of T-cell receptor signaling. Reminiscent of its positional homologue in Epstein-Barr Virus, LMP2A, pK15 may therefore mimic aspects of antigen-receptor signaling. Our findings also suggest that it may be possible to inhibit the recruitment and activation of PLCγ1 pharmacologically.
    Type of Medium: Online Resource
    ISSN: 1553-7374
    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2021
    detail.hit.zdb_id: 2205412-1
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  • 9
    In: JTO Clinical and Research Reports, Elsevier BV, Vol. 4, No. 7 ( 2023-07), p. 100527-
    Type of Medium: Online Resource
    ISSN: 2666-3643
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 3052298-5
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  • 10
    In: Journal of Virology, American Society for Microbiology, Vol. 92, No. 17 ( 2018-09)
    Abstract: Kaposi's sarcoma (KS)-associated herpesvirus (KSHV)/human herpesvirus 8 (HHV-8) causes the angiogenic tumor KS and two B-cell malignancies. The KSHV nonstructural membrane protein encoded by the open reading frame (ORF) K15 recruits and activates several cellular proteins, including phospholipase Cγ1 (PLCγ1), components of the NF-κB pathway, as well as members of the Src family of nonreceptor tyrosine kinases, and thereby plays an important role in the activation of angiogenic and inflammatory pathways that contribute to the pathogenesis of KS as well as KSHV productive (lytic) replication. In order to identify novel cellular components involved in the biology of pK15, we immunoprecipitated pK15 from KSHV-infected endothelial cells and identified associated proteins by label-free quantitative mass spectrometry. Cellular proteins interacting with pK15 point to previously unappreciated cellular processes, such as the endocytic pathway, that could be involved in the function of pK15. We found that the class II phosphatidylinositol 3-kinase (PI3K) PI3K-C2α, which is involved in the endocytosis of activated receptor tyrosine kinases and their signaling from intracellular organelles, interacts and colocalizes with pK15 in vesicular structures abundant in the perinuclear area. Further functional analysis revealed that PI3K-C2α contributes to the pK15-dependent phosphorylation of PLCγ1 and Erk1/2. PI3K-C2α also plays a role in KSHV lytic replication, as evidenced by the reduced expression of the viral lytic genes K-bZIP and ORF45 as well as the reduced release of infectious virus in PI3K-C2α-depleted KSHV-infected endothelial cells. Taken together, our results suggest a role of the cellular PI3K-C2α protein in the functional properties of the KSHV pK15 protein. IMPORTANCE The nonstructural membrane protein encoded by open reading frame K15 of Kaposi's sarcoma-associated herpesvirus (KSHV) (HHV8) activates several intracellular signaling pathways that contribute to the angiogenic properties of KSHV in endothelial cells and to its reactivation from latency. A detailed understanding of how pK15 activates these intracellular signaling pathways is a prerequisite for targeting these processes specifically in KSHV-infected cells. By identifying pK15-associated cellular proteins using a combination of immunoprecipitation and mass spectrometry, we provide evidence that pK15-dependent signaling may occur from intracellular vesicles and rely on the endocytotic machinery. Specifically, a class II PI3K, PI3K-C2α, is recruited by pK15 and involved in pK15-dependent intracellular signaling and viral reactivation from latency. These findings are of importance for future intervention strategies that aim to disrupt the activation of intracellular signaling by pK15 in order to antagonize KSHV productive replication and tumorigenesis.
    Type of Medium: Online Resource
    ISSN: 0022-538X , 1098-5514
    Language: English
    Publisher: American Society for Microbiology
    Publication Date: 2018
    detail.hit.zdb_id: 1495529-5
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