scholarly journals Prediction of biomarkers and therapeutic combinations for anti-PD-1 immunotherapy using the global gene network association

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Chia-Chin Wu ◽  
Y. Alan Wang ◽  
J. Andrew Livingston ◽  
Jianhua Zhang ◽  
P. Andrew Futreal
Keyword(s):  
Tumor Response ◽  
Cytotoxic T Cells ◽  
Gene Signature ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Tumor Resistance ◽  
Patient Response ◽  
Mhc I ◽  
Combination Treatments ◽  
Gene Sets

AbstractOwing to a lack of response to the anti-PD1 therapy for most cancer patients, we develop a network approach to infer genes, pathways, and potential therapeutic combinations that are associated with tumor response to anti-PD1. Here, our prediction identifies genes and pathways known to be associated with anti-PD1, and is further validated by 6 CRISPR gene sets associated with tumor resistance to cytotoxic T cells and targets of the 36 compounds that have been tested in clinical trials for combination treatments with anti-PD1. Integration of our top prediction and TCGA data identifies hundreds of genes whose expression and genetic alterations that could affect response to anti-PD1 in each TCGA cancer type, and the comparison of these genes across cancer types reveals that the tumor immunoregulation associated with response to anti-PD1 would be tissue-specific. In addition, the integration identifies the gene signature to calculate the MHC I association immunoscore (MIAS) that shows a good correlation with patient response to anti-PD1 for 411 melanoma samples complied from 6 cohorts. Furthermore, mapping drug target data to the top genes in our association prediction identifies inhibitors that could potentially enhance tumor response to anti-PD1, such as inhibitors of the encoded proteins of CDK4, GSK3B, and PTK2.

scholarly journals A computational network approach to identify predictive biomarkers and therapeutic combinations for anti-PD-1 immunotherapy in cancer

2020 ◽  
Author(s):  
Chia-Chin Wu ◽  
Y Alan Wang ◽  
J Andrew Livingston ◽  
Jianhua Zhang ◽  
P. Andrew Futreal
Keyword(s):  
Gene Network ◽  
Target Genes ◽  
Tumor Response ◽  
Cytotoxic T Cells ◽  
Predictive Biomarkers ◽  
Cancer Genes ◽  
Network Approach ◽  
Tumor Resistance ◽  
Mhc I ◽  
Transcriptomic Data

AbstractBackgroundDespite remarkable success, only a subset of cancer patients have shown benefit from the anti-PD1 therapy. Therefore, there is a growing need to identify predictive biomarkers and therapeutic combinations for improving the clinical efficacy.ResultsBased upon the hypothesis that aberrations of any gene that are close to MHC class I genes in the gene network are likely to deregulate MHC I pathway and affect tumor response to anti-PD1, we developed a network approach to infer genes, pathway, and potential therapeutic target genes associated with response to PD-1/PD-L1 checkpoint immunotherapies in cancer. Our approach successfully identified genes (e.g. B2M and PTEN) and pathways (e.g. JAK/STAT and WNT) known to be associated with anti-PD1 response. Our prediction was further validated by 5 CRISPR gene sets associated with tumor resistance to cytotoxic T cells. Our results also showed that many cancer genes that act as hubs in the gene network may drive immune evasion through indirectly deregulating the MHC I pathway. The integration analysis of transcriptomic data of the 34 TCGA cancer types and our prediction reveals that MHC I-immunoregulations may be tissue-specific. The signature-based score, the MHC I association immunoscore (MIAS), calculated by integration of our prediction and TCGA melanoma transcriptomic data also showed a good correlation with patient response to anti-PD1 for 354 melanoma samples complied from 5 cohorts. In addition, most targets of the 36 compounds that have been tested in clinical trials or used for combination treatments with anti-PD1 are in the top list of our prediction (AUC=0.833). Integration of drug target data with our top prediction further identified compounds that were recently shown to enhance tumor response to anti-PD1, such as inhibitors of GSK3B, CDK, and PTK2.ConclusionOur approach is effective to identify candidate genes and pathways associated with response to anti-PD-1 therapy, and can also be employed for in silico screening of potential compounds to enhances the efficacy of anti-PD1 agents against cancer.

scholarly journals Bioinformatics Analysis Identifies Precision Treatment with Paclitaxel for Hepatocellular Carcinoma Patients Harboring Mutant TP53 or Wild-Type CTNNB1 Gene

2021 ◽  
Vol 11 (11) ◽  
pp. 1199
Author(s):  
Jiunn-Chang Lin ◽  
Tsang-Pai Liu ◽  
Vivin Andriani ◽  
Muhammad Athoillah ◽  
Chih-Yang Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Mitotic Cell ◽  
Gene Signature ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Wild Type ◽  
Tumor Protein P53 ◽  
Novel Therapeutic Strategies ◽  
Cycle Regulation ◽  
Lower Expression

Hepatocellular carcinoma (HCC) is an aggressive and chemoresistant cancer type. The development of novel therapeutic strategies is still urgently needed. Personalized or precision medicine is a new trend in cancer therapy, which treats cancer patients with specific genetic alterations. In this study, a gene signature was identified from the transcriptome of HCC patients, which was correlated with the patients’ poorer prognoses. This gene signature is functionally related to mitotic cell cycle regulation, and its higher or lower expression is linked to the mutation in tumor protein p53 (TP53) or catenin beta 1 (CTNNB1), respectively. Gene–drug association analysis indicated that the taxanes, such as the clinically approved anticancer drug paclitaxel, are potential drugs targeting this mitotic gene signature. Accordingly, HCC cell lines harboring mutant TP53 or wild-type CTNNB1 genes are more sensitive to paclitaxel treatment. Therefore, our results imply that HCC patients with mutant TP53 or wild-type CTNNB1 genes may benefit from the paclitaxel therapy.

scholarly journals Intratumoral SIRPα-deficient macrophages activate tumor antigen-specific cytotoxic T cells under radiotherapy

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhen Bian ◽  
Lei Shi ◽  
Koby Kidder ◽  
Ke Zen ◽  
Charlie Garnett-Benson ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Response ◽  
Cytotoxic T Cells ◽  
Suppressor Cells ◽  
Myeloid Derived Suppressor Cells ◽  
Tumor Resistance ◽  
Treatment Resistant ◽  
Humoral And Cellular Immunity ◽  
Advanced Stages ◽  
Post Radiation

AbstractRadiotherapy (RT)-induced tumoricidal immunity is severely limited when tumors are well-established. Here, we report that depleting SIRPα on intratumoral macrophages augments efficacy of RT to eliminate otherwise large, treatment-resistant colorectal (MC38) and pancreatic (Pan02 and KPC) tumors, inducing complete abscopal remission and long-lasting humoral and cellular immunity that prevent recurrence. SIRPα-deficient macrophages activated by irradiated tumor-released DAMPs exhibit robust efficacy and orchestrate an anti-tumor response that controls late-stage tumors. Upon RT-mediated activation, intratumoral SIRPα-deficient macrophages acquire potent proinflammatory features and conduct immunogenic antigen presentation that confer a tumoricidal microenvironment highly infiltrated by tumor-specific cytotoxic T cells, NK cells and inflammatory neutrophils, but with limited immunosuppressive regulatory T cells, myeloid derived suppressor cells and post-radiation wound-healing. The results demonstrate that SIRPα is a master regulator underlying tumor resistance to RT and provide proof-of-principle for SIRPα-deficient macrophage-based therapies to treat a broad spectrum of cancers, including those at advanced stages with low immunogenicity and metastases.

scholarly journals Genetic mechanisms of HLA-I loss and immune escape in diffuse large B cell lymphoma

2021 ◽  
Vol 118 (22) ◽  
pp. e2104504118
Author(s):  
Marco Fangazio ◽  
Erik Ladewig ◽  
Karen Gomez ◽  
Laura Garcia-Ibanez ◽  
Rahul Kumar ◽  
...  
Keyword(s):  
B Cell ◽  
Immune Escape ◽  
Cell Lymphoma ◽  
Cytotoxic T Cells ◽  
B Cell Lymphoma ◽  
Genetic Alterations ◽  
Cell Surface Expression ◽  
Mhc I ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Fifty percent of diffuse large B cell lymphoma (DLBCL) cases lack cell-surface expression of the class I major histocompatibility complex (MHC-I), thus escaping recognition by cytotoxic T cells. Here we show that, across B cell lymphomas, loss of MHC-I, but not MHC-II, is preferentially restricted to DLBCL. To identify the involved mechanisms, we performed whole exome and targeted HLA deep-sequencing in 74 DLBCL samples, and found somatic inactivation of B2M and the HLA-I loci in 80% (34 of 42) of MHC-INEG tumors. Furthermore, 70% (22 of 32) of MHC-IPOS DLBCLs harbored monoallelic HLA-I genetic alterations (MHC-IPOS/mono), indicating allele-specific inactivation. MHC-INEG and MHC-IPOS/mono cases harbored significantly higher mutational burden and inferred neoantigen load, suggesting potential coselection of HLA-I loss and sustained neoantigen production. Notably, the analysis of >500,000 individuals across different cancer types revealed common germline HLA-I homozygosity, preferentially in DLBCL. In mice, germinal-center B cells lacking HLA-I expression did not progress to lymphoma and were counterselected in the context of oncogene-driven lymphomagenesis, suggesting that additional events are needed to license immune evasion. These results suggest a multistep process of HLA-I loss in DLBCL development including both germline and somatic events, and have direct implications for the pathogenesis and immunotherapeutic targeting of this disease.

823 CD4 T cells are essential for an anti-tumor effect in a B78 murine melanoma tumor model

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A873-A873
Author(s):  
Arika Feils ◽  
Mackenzie Heck ◽  
Anna Hoefges ◽  
Peter Carlson ◽  
Luke Zangl ◽  
...  
Keyword(s):  
T Cells ◽  
Tumor Growth ◽  
Cd4 T Cells ◽  
Tumor Response ◽  
Immune Cell ◽  
Cd8 T Cell ◽  
Mhc I ◽  
Mhc Ii ◽  
Flow Cytometric

BackgroundMice bearing B78 melanoma tumors can be cured using an in situ vaccine (ISV) regimen that includes radiation (RT) together with immunocytokine (tumor-targeting mAb conjugated to IL-2). B78 melanoma cells, derived from B16 cells, express minimal to no MHC-I but express MHC-II upon IFN-g/TNF-a stimulation. Although B78 cells are primarily MHC-I-deficient, an increased CD8 T cell infiltration into the tumor microenvironment (TME) has been shown following ISV.1 To further investigate the potential role of specific immune cell lineages in the B78 anti-tumor response to ISV, immune subset depletion studies and flow cytometric analyses were performed.MethodsC57BL/6 mice bearing B78 tumors were depleted of immune cell subsets with mAbs (anti-CD4, anti-CD8, anti-NK1.1, or Rat IgG control) for 3 weeks during the course of treatment. Treatment groups included no treatment, RT (12 Gy), or ISV (RT D0 and immunocytokine D5-D9). 6 mice/group (repeated three times) were followed for survival/tumor growth, and flow cytometry studies included 4 mice/group, sacrificed on D8 and D13 following the start of ISV.ResultsMice depleted of CD4 T cells during the course of ISV showed a significant reduction of anti-tumor effect as compared to mice treated with ISV/Rat IgG (pConclusionsThese studies suggest that CD4 T cells are essential for an anti-tumor response in the B78 melanoma model. In vivo depletion data show that CD4 T cells, but not CD8 or NK cells, are required for a decrease in tumor growth via ISV. Flow cytometric analyses suggest an interplay between CD4 and CD8 T cells as indicated by a decrease in CD8/IFN-g expression following ISV in the absence of CD4 T cells. The role that MHC-I and MHC-II expression plays in this CD4/CD8 T cell anti-tumor response is under investigation. In future studies, B78 melanoma may serve as a critical syngeneic model for development of more effective immunotherapy treatment regimens.Ethics ApprovalAll animal experiments were performed in accordance with protocols approved by Animal Care and Use Committees of the University of Wisconsin-Madison.ReferenceMorris Z, Guy E, Francis D, et al. In situ tumor vaccination by combining local radiation and tumor-specific antibody or immunocytokine treatments. Cancer Res 2016;76(13):3929-3941.

scholarly journals Tumor cell total mRNA expression shapes the molecular and clinical phenotype of cancer

2021 ◽  
Author(s):  
Shaolong Cao ◽  
Jennifer Wang ◽  
Shuangxi Ji ◽  
Peng Yang ◽  
Matthew Montierth ◽  
...  
Keyword(s):  
Tumor Cell ◽  
Mrna Expression ◽  
Genetic Alterations ◽  
Individual Variability ◽  
Cancer Type ◽  
Sequencing Data ◽  
Increased Risk ◽  
Mrna Content ◽  
Risk Of Disease ◽  
Pan Cancer

Abstract Cancers can vary greatly in their transcriptomes. In contrast to alterations in specific genes or pathways, differences in tumor cell total mRNA content have not been comprehensively assessed. Technical and analytical challenges have impeded examination of total mRNA expression at scale across cancers. To address this, we developed a model for quantifying tumor-specific total mRNA expression (TmS) from bulk sequencing data, which performs transcriptomic deconvolution while adjusting for mixed genomes. We used single-cell RNA sequencing data to demonstrate total mRNA expression as a feature of tumor phenotype. We estimated and validated TmS in 5,015 patients across 15 cancer types identifying significant inter-individual variability. At a pan-cancer level, high TmS is associated with increased risk of disease progression and death. Cancer type-specific patterns of genetic alterations, intra-tumor genetic heterogeneity, as well as pan-cancer trends in metabolic dysregulation and hypoxia contribute to TmS. Taken together, our results suggest that measuring cell-type specific total mRNA expression offers a broader perspective of tracking cancer transcriptomes, which has important biological and clinical implications.

scholarly journals Analyzing cancer gene expression data through the lens of normal tissue-specificity

2021 ◽  
Author(s):  
H. Robert Frost
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Tissue Specificity ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Tissue Specific ◽  
Normal Tissues ◽  
Cancer Types

AbstractThe genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

scholarly journals From Genetic Alterations to Tumor Microenvironment: The Ariadne’s String in Pancreatic Cancer

Cells ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 309 ◽  
Author(s):  
Chiara Bazzichetto ◽  
Fabiana Conciatori ◽  
Claudio Luchini ◽  
Francesca Simionato ◽  
Raffaela Santoro ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Microenvironment ◽  
Current Knowledge ◽  
Myeloid Cells ◽  
Genetic Alterations ◽  
Molecular Characteristics ◽  
Precision Oncology ◽  
Cancer Type ◽  
Tumor Type ◽  
Driver Genes

The threatening notoriety of pancreatic cancer mainly arises from its negligible early diagnosis, highly aggressive progression, failure of conventional therapeutic options and consequent very poor prognosis. The most important driver genes of pancreatic cancer are the oncogene KRAS and the tumor suppressors TP53, CDKN2A, and SMAD4. Although the presence of few drivers, several signaling pathways are involved in the oncogenesis of this cancer type, some of them with promising targets for precision oncology. Pancreatic cancer is recognized as one of immunosuppressive phenotype cancer: it is characterized by a fibrotic-desmoplastic stroma, in which there is an intensive cross-talk between several cellular (e.g., fibroblasts, myeloid cells, lymphocytes, endothelial, and myeloid cells) and acellular (collagen, fibronectin, and soluble factors) components. In this review; we aim to describe the current knowledge of the genetic/biological landscape of pancreatic cancer and the composition of its tumor microenvironment; in order to better direct in the intrinsic labyrinth of this complex tumor type. Indeed; disentangling the genetic and molecular characteristics of cancer cells and the environment in which they evolve may represent the crucial step towards more effective therapeutic strategies

scholarly journals Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach

Open Physics ◽  
2009 ◽  
Vol 7 (3) ◽  
Author(s):  
Nicola Pizzolato ◽  
Davide Valenti ◽  
Dominique Adorno ◽  
Bernardo Spagnolo
Keyword(s):  
Cancer Progression ◽  
Blood Cells ◽  
Evolutionary Dynamics ◽  
Kinase Inhibitor ◽  
Stochastic Approach ◽  
Progressive Increase ◽  
Genetic Alterations ◽  
Leukemic Cells ◽  
Patient Response ◽  
Cancerous Cells

AbstractThe evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-treated leukemic cells are described as a consequence of the efficacy of the different modelled therapies. We show how the patient response to the therapy changes when a high value of the mutation rate from healthy to cancerous cells is present. Our results are in agreement with clinical observations. Unfortunately, development of resistance to imatinib is observed in a fraction of patients, whose blood cells are characterized by an increasing number of genetic alterations. We find that the occurrence of resistance to the therapy can be related to a progressive increase of deleterious mutations.

Circulating tumor DNA molecular profiling in rare cancer patients from the MASTER KEY Project.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e14532-e14532
Author(s):  
Hitomi Sumiyoshi Okuma ◽  
Kan Yonemori ◽  
Takuji Seo ◽  
Emi Noguchi ◽  
Keiko Wakakuwa ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Salivary Gland Tumor ◽  
Circulating Tumor Dna ◽  
Genetic Alterations ◽  
Unknown Primary ◽  
Genomic Alteration ◽  
Cancer Type ◽  
Rare Cancer ◽  
Registry Study ◽  
Tumor Dna

e14532 Background: In April 2017, MASTER KEY Project, composed of a prospective registry study part and a multiple clinical trials part, was established to promote treatment development for rare cancers, which is lacking standard or investigational therapeutic options. Circulating tumor DNA (ctDNA) analysis by next-generation sequencing (NGS) has provided new insight into personalized medicine in a more accessible, non-invasive manner; however, most reports are focused on common cancers. We report genetic alterations detected by ctDNA NGS analysis in rare solid cancers. Methods: Prospectively consented patients (pts), also enrolled in MASTER KEY registry study, had ctDNA NGS testing at a CLIA-certified lab (Guardant360) for point mutations, indels, copy number amplifications, fusions, and microsatellite instability. Alterations were assessed for incidence according to cancer type, functional impact, therapeutic implications, and comparison with tissue NGS. Main inclusion criteria: 1) age ≥16, 2) histological diagnosis of rare cancer (annual incidence less than 6 cases per 100,000 population), cancer of unknown primary (CUP), or rare tissue subtypes of common cancers, 3) active metastatic / unresectable cancer, 4) a written consent. Results: From Nov. 2018 to Jan 2019, 50 pts had Guardant360 testing. Diseases included: soft tissue sarcoma (28), ovarian carc. (7), CUP (4), salivary gland tumor (3), thyroid carc. (2), GIST (1), adrenal cortical carc. (1), rare subtype of GI tract (1), malignant mesothelioma (1), nephroblastoma (1), NET (1), NUT carc. (1). All Japanese, male/female = 14/36, median age 61, ECOG performance status 0/1/2/3 = 30/19/0/1. 76% of pts (38/50) had ≥1 alteration detected, with median number of 2 alterations (range: 0-9), with VAF(0.1-60.3%); 87%(33/38) of those pts had a variant most likely pathogenic; 61% (20/33) of those pts had a variant potential for clinical action. Mean TAT was 10.3 days. 19 pts had tissue NGS testing and in 3 pts, alterations were detected by ctDNA NGS but not by tissue NGS. Updated results of 100 patients will be presented at the conference. Conclusions: Most rare cancer patients with advanced disease had a detectable genomic alteration by Guardant360. Clinical trial information: UMIN000034394.

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