scholarly journals A Comprehensive Pan-Cancer Analysis of RBM8A Based on Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Nan Mei ◽  
Heyan Chen ◽  
Ni Zhao ◽  
Ye Yi ◽  
Chunli Li
Keyword(s):  
Rna Binding ◽  
Checkpoint Inhibitors ◽  
Study Data ◽  
Binding Motif ◽  
Exon Junction Complex ◽  
Tumor Type ◽  
Missense Mutations ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Cancer Types

Background. As a member of the exon junction complex (EJC), RNA-binding motif protein 8A (RBM8A) plays a crucial role in the maintenance of mRNA and multiple activities of an organism. Immunotherapy has been proven to be a staple type of cancer treatment. However, the role of RBM8A and immunity across cancer types is unclear. Objective. This study aims to visualize the expression, prognosis, mutations, and coexpressed gene results of RBM8A across cancer types and to explore the link between RBM8A expression and immunity. Methods. In this study, data were collected from multiple online databases. We analyzed the data using the HPA, UALCAN Database, COSMIC, cBioPortal, Cancer Regulome tools, Kaplan–Meier Plotter, and TIMER website. Results. For the expression of RBM8A in normal tissues, higher expression of RBM8A was observed in immune-related cells than in nonimmune organs. The expression level of RBM8A was related to tumor type. Missense mutations in RBM8A were found in most tumors and affected the prognosis of carcinomas with coexpressed genes. RBM8A was strongly associated with immune-infiltrating cells and immune checkpoint inhibitors, especially in LIHC. Conclusions. RBM8A is a gene worth exploring and may be a unique immune target in the future.

scholarly journals Pan-cancer analysis of CD274 (PD-L1) mutations in 314,631 patient samples and subset correlation with PD-L1 protein expression

2021 ◽  
Vol 9 (6) ◽  
pp. e002558
Author(s):  
Richard S.P. Huang ◽  
Brennan Decker ◽  
Karthikeyan Murugesan ◽  
Matthew Hiemenz ◽  
Douglas A. Mata ◽  
...  
Keyword(s):  
Protein Expression ◽  
Checkpoint Inhibitors ◽  
Endometrial Adenocarcinoma ◽  
Primary Melanoma ◽  
B Cell Lymphoma ◽  
Unknown Primary ◽  
Future Research ◽  
Tumor Type ◽  
Missense Mutations ◽  
L1 Protein

BackgroundThe effects of non-amplification short variant (SV) mutations in CD274 (programmed death-ligand 1 (PD-L1)) on PD-L1 protein expression and immune checkpoint inhibitors (ICPIs) therapy are unknown. Here, we present a retrospective analysis of CD274 mutations detected by comprehensive genomic profiling (CGP) and correlate these results with tumor-cell PD-L1 immunohistochemistry (IHC)-based expression assessment to better understand the relationship between mutations and protein expression of PD-L1.MethodsCGP was performed on hybridization-captured, adaptor ligation-based libraries using DNA and/or RNA extracted from 314,631 tumor samples that were sequenced for up to 406 cancer-related genes and select gene rearrangements. PD-L1 IHC was performed on a subset of cases (n=58,341) using the DAKO 22C3 PD-L1 IHC assay and scored with the tumor proportion score (TPS).ResultsOverall, the prevalence of CD274 SV mutations was low (0.3%, 1081/314,631) with 577 unique variants. The most common CD274 SV mutations were R260H (n=51), R260C (n=18), R125Q (n=12), C272fs*13 (n=11), R86W (n=10), and R113H (n=10). The prevalence of CD274 mutations varied depending on tumor type with diffuse large B-cell lymphoma (1.9%, 19/997), cutaneous squamous cell carcinoma (1.6%, 14/868), endometrial adenocarcinoma (1.0%, 36/3740), unknown primary melanoma (0.9%, 33/3679), and cutaneous melanoma (0.8%, 32/3874) having the highest frequency of mutations. Of the R260H cases concurrently tested with PD-L1 IHC, most (81.8%, 9/11) had no PD-L1 expression, which contrasts to the five E237K cases where most (80%, 4/5) had PD-L1 expression. In addition, we saw a significantly lower level of PD-L1 expression in samples with a clonal truncating variant (nonsense or frameshift indel) when compared with samples with a subclonal truncating variants (mean: TPS=1 vs TPS=38; p<0.001), and also in clonal versus subclonal missense mutations (mean: TPS=11 vs TPS=22, respectively; p=0.049)ConclusionsWe defined the landscape of CD274 mutations in a large cohort of tumor types that can be used as a reference for examining CD274 mutations as potential resistance biomarkers for ICPI. Furthermore, we presented novel data on the correlation of CD274 mutations and PD-L1 protein expression, providing important new information on the potential functionality of these mutations and can serve as a basis for future research.

Tissue tumor mutational burden (TMB) as a biomarker of efficacy with immune checkpoint inhibitors (ICI) in metastatic gastrointestinal (mGI) cancers.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e14559-e14559
Author(s):  
Robert William Lentz ◽  
Tyler Friedrich ◽  
Junxiao Hu ◽  
Alexis Diane Leal ◽  
Sunnie S. Kim ◽  
...  
Keyword(s):  
Checkpoint Inhibitors ◽  
Objective Response ◽  
Retrospective Chart Review ◽  
Progression Free Survival ◽  
Predictive Biomarker ◽  
Continuous Variable ◽  
Tumor Type ◽  
Logistic Regression Models ◽  
Kaplan Meier ◽  
Academic Center

e14559 Background: While TMB is very dependent on methodology, tissue TMB-H (≥10 mutations/megabase) may predict benefit with ICIs. Pembrolizumab received tissue-agnostic approval for TMB-H unresectable cancers in 2020, but little is known about TMB as a predictive biomarker in mGI cancers. We hypothesized that tissue TMB will correlate with efficacy of ICIs in mGI cancers. Methods: A retrospective chart review identified patients with mGI cancers who received an anti-PD-(L)1 drug and had known TMB at a single academic center from 2012 to 2020. The association of TMB with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS) was analyzed using the Fisher’s exact and Log-rank tests. Survival curves were generated using the Kaplan-Meier method. Cox proportional hazard and logistic regression models were used to adjust for microsatellite status. Significance was prespecified at 0.05. Results: 83 patients were identified and included. The most common cancer types were colorectal adenocarcinoma (AC, n = 29), esophageal/gastric AC (n = 21) and SCC (n = 4), cholangiocarcinoma (n = 11), anal SCC (n = 7), and pancreas AC (n = 7). Average age was 61, average number of lines of prior systemic therapy for advanced disease was 1.3 (range 0-4), and 37% of patients were treated on a clinical study. All patients received an anti-PD-(L)1 drug; 6%, 2%, and 36% also received ipilimumab, cytotoxic chemotherapy, and other combinations, respectively. Among those with esophageal/gastric cancer, 76% had known PD-L1 CPS (84% ≥1, 63% ≥5, 42% ≥10). TMB was primarily determined by Foundation One CDx (87%). TMB ranged from 0 to 54; n = 22 (27%) were TMB-H (of these, n = 10 were microsatellite instability-high (MSI-H)), and n = 61 were TMB-L ( < 10 mutations/megabase; of these, n = 2 were MSI-H). The prevalence of TMB-H and microsatellite stable (MSS) was 14.4%. TMB-L, compared to TMB-H, was associated with inferior ORR (3.5% vs 55.6%; odds ratio (OR) 0.045; p < 0.001) and PFS (median 12.7 vs 29.3 weeks; hazard ratio (HR) 2.70; p = 0.001), but not OS (HR 1.20; p = 0.60). In patients with MSS disease, TMB-L, compared to TMB-H, was associated with inferior ORR (OR 0.13; p = 0.04) but not PFS (HR 1.76; p = 0.07) or OS (HR 0.89; p = 0.79). In subgroup analyses, ORR was not significantly associated to tumor type in all or MSS patients. TMB as a continuous variable, in patients with MSS disease, was positively correlated with ORR (p = 0.02) and PFS (p = 0.04), but not OS (p = 0.59). Among all patients, PFS and OS data is immature (median follow-up 13 and 31 weeks). Conclusions: In a single center retrospective study of patients with mGI cancers treated with ICIs, TMB-H was associated with improved ORR and PFS compared to TMB-L. In patients with MSS disease, ORR remained significant. PFS and OS data are immature. TMB as a biomarker of efficacy with ICIs in mGI cancers warrants further study to guide clinical use.

scholarly journals Biomarkers for Predicting Response to Immunotherapy with Immune Checkpoint Inhibitors in Cancer Patients

2019 ◽  
Vol 65 (10) ◽  
pp. 1228-1238 ◽  
Author(s):  
Michael J Duffy ◽  
John Crown
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Future Research ◽  
Specific Gene ◽  
Tumor Type ◽  
Clinical Use ◽  
Durable Response ◽  
Cancer Types

Abstract BACKGROUND Immunotherapy, especially the use of immune checkpoint inhibitors, has revolutionized the management of several different cancer types in recent years. However, for most types of cancer, only a minority of patients experience a durable response. Furthermore, administration of immunotherapy can result in serious adverse reactions. Thus, for the most efficient and effective use of immunotherapy, accurate predictive biomarkers that have undergone analytical and clinical validation are necessary. CONTENT Among the most widely investigated predictive biomarkers for immunotherapy are programmed death-ligand 1 (PD-L1), microsatellite instability/defective mismatch repair (MSI/dMMR), and tumor mutational burden (TMB). MSI/dMMR is approved for clinical use irrespective of the tumor type, whereas PD-L1 is approved only for use in certain cancer types (e.g., for predicting response to first-line pembrolizumab monotherapy in non-small cell lung cancer). Although not yet approved for clinical use, TMB has been shown to predict response to several different forms of immunotherapy and across multiple cancer types. Less widely investigated predictive biomarkers for immunotherapy include tumor-infiltrating CD8+ lymphocytes and specific gene signatures. Despite being widely investigated, assays for MSI/dMMR, PD-L1, and TMB lack standardization and are still evolving. An urgent focus of future research should be the optimization and standardization of method for determining these biomarkers. SUMMARY Biomarkers for predicting response to immunotherapy are paving the way for personalized treatment for patients with diverse cancer types. However, standardization of the available biomarker assays is an urgent requirement.

scholarly journals Gain-of-function cardiomyopathic mutations in RBM20 rewire splicing regulation and re-distribute ribonucleoprotein aggregates within processing bodies

2021 ◽  
Author(s):  
Aidan M Fenix ◽  
Yuichiro Miyaoka ◽  
Alessandro Bertero ◽  
Steven Blue ◽  
Matthew J Spindler ◽  
...  
Keyword(s):  
Rna Binding ◽  
Acute Stress ◽  
Rna Binding Proteins ◽  
Super Resolution ◽  
Circular Rna ◽  
Binding Motif ◽  
Missense Mutations ◽  
Gain Of Function ◽  
Processing Bodies ◽  
Heart Pathology

RNA binding motif protein 20 (RBM20) is a key regulator of alternative splicing in the heart, and its mutation leads to malignant dilated cardiomyopathy (DCM). To understand the mechanism of RBM20-associated DCM, we engineered isogenic human induced pluripotent stem cells (iPSCs) with heterozygous or homozygous DCM-associated missense mutations in RBM20 (R636S) as well as RBM20 knockout (KO) iPSCs. iPSC-derived engineered heart tissues made from these cell lines recapitulated contractile dysfunction of RBM20-associated DCM and revealed greater dysfunction with missense mutations than KO. Analysis of RBM20 RNA binding by eCLIP revealed a gain-of-function preference of mutant RBM20 for 3′ UTR sequences that are shared with amyotrophic lateral sclerosis (ALS) and processing-body associated RNA binding proteins (FUS, DDX6). Deep RNA sequencing revealed that the RBM20 R636S mutant has unique gene, splicing, polyadenylation and circular RNA defects that differ from RBM20 KO, impacting distinct cardiac signaling pathways. Splicing defects specific to KO or R636S mutations were supported by data from R636S gene-edited pig hearts and eCLIP. Super-resolution microscopy verified that mutant RBM20 maintains limited nuclear localization potential; rather, the mutant protein associates with cytoplasmic processing bodies (DDX6) under basal conditions, and with stress granules (G3BP1) following acute stress. Taken together, our results highlight a novel pathogenic mechanism in cardiac disease through splicing-dependent and -independent pathways that are likely to mediate differential contractile phenotypes and stress-associated heart pathology.

scholarly journals 330 Integration of molecular cancer classification and next-generation sequencing to identify metastatic patients eligible for immune checkpoint inhibitors

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A356-A356
Author(s):  
Daruka Mahadevan ◽  
Li Ma ◽  
Kai Treuner ◽  
Jenna Wong ◽  
Catherine Schnabel
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Tumor Type ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Biomarker Testing ◽  
Cancer Types ◽  
Tumor Types

BackgroundImmune checkpoint inhibitors (ICIs) have improved patient outcomes and are a new standard of care for treating a variety of cancers. Eligibility for ICIs is established through determination of tumor type and use of predictive biomarkers. PD-L1, microsatellite instability (MSI), and tumor mutation burden (TMB) are FDA-approved predictive biomarkers for ICI therapies. However, the validity of these biomarkers remains controversial, as studies have shown a failure to predict ICI response in many cancer types.1 2 The 92-gene assay (CancerTYPE ID) is a validated gene expression classifier of 50 tumor types and subtypes for metastatic patients with ambiguous diagnoses. CancerTYPE ID provides critical cancer type identification to guide ICI treatment eligibility and selection. In the current study, analyses integrating tumor type with multimodal biomarker testing for PD-L1 and TMB were evaluated to identify patients for ICI eligibility.MethodsMOSAIC (Molecular Synergy to Advance Individualized Cancer Care) is an IRB-approved, de-identified database of CancerTYPE ID results from 2572 patients with tumor-specific multimodal biomarker testing by next-generation sequencing for TMB and immunohistochemistry for PD-L1. The Cochran-Mantel-Haenszel test was used to evaluate the relationship between PD-L1 and TMB across tumor types.ResultsTumor type was determined in 2377 of 2572 cases (92.4%), comprising 27 different tumor types including 14 tumor types with FDA-approved ICI therapies. Among the top 20 tumor types, PD-L1 was present in a larger proportion of tumors (weighted mean=78.9%, range=58.3%–100%) versus TMB (20.9%, 0%–72.7%) (figure 1). Varying expression levels of PD-L1 and TMB were noted across tumor types (Figure 1), and no relationship between PD-L1 and TMB (P=0.15) was observed. Prevalence of high TMB in melanoma (42.9%) and lung adenocarcinoma (38.9%), which are more likely to respond to ICI treatment, are consistent with published data; however, prevalence of high TMB in mesothelioma (20.0%), sarcoma (23.6%) and prostatic adenocarcinoma (33.3%), which are not likely to respond to ICI treatment, are higher than previously reported.3Abstract 330 Figure 1Prevalence of PD-L1 expression and high TMB in the 27 identified tumor typesConclusionsTumor type classification and cellular context are critical for ICI eligibility. CancerTYPE ID successfully differentiated 14 ICI-eligible tumor types from 13 non-ICI-eligible tumor types. Further, since there is no relationship between PD-L1 and TMB for different tumor types, accurate tumor type identification is necessary to select the most appropriate biomarker. This highlights the clinical utility of CancerTYPE ID combined with multimodal biomarker testing to guide ICI treatment and predict response based on tumor type identification, which may improve outcomes in patients with metastatic cancer.ReferencesMcGrail DJ, Pilié PG, Rashid NU, et al. High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann Oncol 2021;32(5):661–672.Gjoerup O, Brown CA, Ross JS, et al. Identification and utilization of biomarkers to predict response to immune checkpoint inhibitors. AAPS J 2020;22(6):132.Yarchoan M, Albacker LA, Hopkins AC, et al. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 2019;4(6):e126908.

scholarly journals The human tumor microbiome is composed of tumor type–specific intracellular bacteria

Science ◽  
2020 ◽  
Vol 368 (6494) ◽  
pp. 973-980 ◽  
Author(s):  
Deborah Nejman ◽  
Ilana Livyatan ◽  
Garold Fuks ◽  
Nancy Gavert ◽  
Yaara Zwang ◽  
...  
Keyword(s):  
Smoking Status ◽  
Human Tumor ◽  
Comprehensive Analysis ◽  
Intracellular Bacteria ◽  
Tumor Type ◽  
Microbiome Composition ◽  
Normal Tissues ◽  
Cancer Types ◽  
Tumor Types

Bacteria were first detected in human tumors more than 100 years ago, but the characterization of the tumor microbiome has remained challenging because of its low biomass. We undertook a comprehensive analysis of the tumor microbiome, studying 1526 tumors and their adjacent normal tissues across seven cancer types, including breast, lung, ovary, pancreas, melanoma, bone, and brain tumors. We found that each tumor type has a distinct microbiome composition and that breast cancer has a particularly rich and diverse microbiome. The intratumor bacteria are mostly intracellular and are present in both cancer and immune cells. We also noted correlations between intratumor bacteria or their predicted functions with tumor types and subtypes, patients’ smoking status, and the response to immunotherapy.

scholarly journals The co-expression networks of differentially expressed RBPs with TFs and LncRNAs related to clinical TNM stages of cancers

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7696 ◽  
Author(s):  
Shuaibin Lian ◽  
Liansheng Li ◽  
Yongjie Zhou ◽  
Zixiao Liu ◽  
Lei Wang
Keyword(s):  
Cluster Analysis ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
Correlation Networks ◽  
Expression Cluster ◽  
Cancer Types ◽  
Almost All ◽  
Insight Into

Background RNA-binding proteins (RBPs) play important roles in cellular homeostasis by regulating the expression of thousands of transcripts, which have been reported to be involved in human tumorigenesis. Despite previous reports of the dysregulation of RBPs in cancers, the degree of dysregulation of RBPs in cancers and the intrinsic relevance between dysregulated RBPs and clinical TNM information remains unknown. Furthermore, the co-expressed networks of dysregulated RBPs with transcriptional factors and lncRNAs also require further investigation. Results Here, we firstly analyzed the deviations of expression levels of 1,542 RBPs from 20 cancer types and found that (1) RBPs are dysregulated in almost all 20 cancer types, especially in BLCA, COAD, READ, STAD, LUAD, LUSC and GBM with proportion of deviation larger than 300% compared with non-RBPs in normal tissues. (2) Up- and down-regulated RBPs also show opposed patterns of differential expression in cancers and normal tissues. In addition, down-regulated RBPs show a greater degree of dysregulated expression than up-regulated RBPs do. Secondly, we analyzed the intrinsic relevance between dysregulated RBPs and clinical TNM information and found that (3) Clinical TNM information for two cancer types—CHOL and KICH—is shown to be closely related to patterns of differentially expressed RBPs (DE RBPs) by co-expression cluster analysis. Thirdly, we identified ten key RBPs (seven down-regulated and three up-regulated) in CHOL and seven key RBPs (five down-regulated and two up-regulated) in KICH by analyzing co-expression correlation networks. Fourthly, we constructed the co-expression networks of key RBPs between 1,570 TFs and 4,147 lncRNAs for CHOL and KICH, respectively. Conclusions These results may provide an insight into the understanding of the functions of RBPs in human carcinogenesis. Furthermore, key RBPs and the co-expressed networks offer useful information for potential prognostic biomarkers and therapeutic targets for patients with cancers at the N and M stages in two cancer types CHOL and KICH.

Antibiotics prescription to decrease progression-free survival (PFS) and overall survival (OS) in patients with advanced cancers treated with PD1/PDL1 immune checkpoint inhibitors.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 3015-3015 ◽  
Author(s):  
Lisa Derosa ◽  
Bertrand Routy ◽  
Laura Mezquita ◽  
Charles Naltet ◽  
David Enot ◽  
...  
Keyword(s):  
Risk Factors ◽  
Immune Checkpoint ◽  
Cox Regression ◽  
Negative Impact ◽  
Checkpoint Inhibitors ◽  
Progression Free Survival ◽  
Cancer Type ◽  
Tumor Type ◽  
Kaplan Meier ◽  
The Impact

3015 Background: Use of antibiotics (ATB) alters the gut microbiota composition and decreases bacterial diversity. Pre-clinical evidences demonstrated the impact of the microbiota in the efficacy of immune checkpoint blockades (ICB) in cancer. Interaction between ATB and ICB has not been extensively investigated in cancer patients (pts). Our study evaluated the effect of ATB in cancer pts treated with PD-1/PD-L1 inhibitors. Methods: We conducted a retrospective analysis of pts treated with PD-1/PD-L1 inhibitors for advanced Renal Cell Carcinoma (RCC), Urothelial Cancer (UC) and Non-Small Cell Lung Cancer (NSCLC) and data on ATB use were collected. ATB(+)/(-) groups were defined as pts treated or not with ATB before (2 months period) or within the first month of ICB. PFS and OS were compared between both groups among all pts and then according to tumor site. Statistical analyses were performed using the Kaplan-Meier method. Cox regression analyses were performed separately for each cancer type adjusting for its specific risk factors. Results: Among 175 pts included, 51 (29%) received ATB (mostly beta-lactamases and fluoroquinolones). ATB(+) group had shorter PFS and OS when compared to ATB(-) group: 3.4 vs. 5.2 months, p < 0.013, and 12.2 vs. 20.8 months, p < 0.001, respectively. According to tumor type, ATB(+) group translated into decrease OS (7.0 vs. 13.8 months, p < 0.038) in NSCLC. In RCC and UC pts, ATB (+) group had shorter PFS when compared to ATB(-) group (4.3 vs. 7.4 months, p < 0.013 and 1.8 vs. 4.3 months, p = 0.048, respectively). The negative impact of ATB was maintained after multivariate analyses adjusting for risk factors in each tumor type. Conclusions: ATB prescription preceding or concomitant to the first injection of PD-1/PD-L1 inhibitors impaired the outcome in patients with advanced cancers. This reduction in efficacy seems to be independent of classical prognostic factors in RCC, UC and NSCLC. These data should be validated in larger cohort. In addition, the role of gut composition to explain this interaction is ongoing, as well as novel diagnosis tools based on microbiota to predict response/resistance to ICB.

Immune Checkpoint Inhibitors: Basics and Challenges

2019 ◽  
Vol 26 (17) ◽  
pp. 3009-3025 ◽  
Author(s):  
Bin Li ◽  
Ho Lam Chan ◽  
Pingping Chen
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Complete Response ◽  
Modern World ◽  
Basic Principles ◽  
Mutation Status ◽  
Anti Cancer ◽  
Cancer Types ◽  
Shed Light

Cancer is one of the most deadly diseases in the modern world. The last decade has witnessed dramatic advances in cancer treatment through immunotherapy. One extremely promising means to achieve anti-cancer immunity is to block the immune checkpoint pathways – mechanisms adopted by cancer cells to disguise themselves as regular components of the human body. Many review articles have described a variety of agents that are currently under extensive clinical evaluation. However, while checkpoint blockade is universally effective against a broad spectrum of cancer types and is mostly unrestricted by the mutation status of certain genes, only a minority of patients achieve a complete response. In this review, we summarize the basic principles of immune checkpoint inhibitors in both antibody and smallmolecule forms and also discuss potential mechanisms of resistance, which may shed light on further investigation to achieve higher clinical efficacy for these inhibitors.

NOB1: A Potential Biomarker or Target in Cancer

2019 ◽  
Vol 20 (10) ◽  
pp. 1081-1089
Author(s):  
Weiwei Ke ◽  
Zaiming Lu ◽  
Xiangxuan Zhao
Keyword(s):  
Cancer Treatment ◽  
Molecular Mechanisms ◽  
Rna Binding ◽  
Binding Protein ◽  
Tumor Development ◽  
Anticancer Therapy ◽  
Research Progress ◽  
Normal Tissues ◽  
Potential Biomarker

Human NIN1/RPN12 binding protein 1 homolog (NOB1), an RNA binding protein, is expressed ubiquitously in normal tissues such as the lung, liver, and spleen. Its core physiological function is to regulate protease activities and participate in maintaining RNA metabolism and stability. NOB1 is overexpressed in a variety of cancers, including pancreatic cancer, non-small cell lung cancer, ovarian cancer, prostate carcinoma, osteosarcoma, papillary thyroid carcinoma, colorectal cancer, and glioma. Although existing data indicate that NOB1 overexpression is associated with cancer growth, invasion, and poor prognosis, the molecular mechanisms behind these effects and its exact roles remain unclear. Several studies have confirmed that NOB1 is clinically relevant in different cancers, and further research at the molecular level will help evaluate the role of NOB1 in tumors. NOB1 has become an attractive target in anticancer therapy because it is overexpressed in many cancers and mediates different stages of tumor development. Elucidating the role of NOB1 in different signaling pathways as a potential cancer treatment will provide new ideas for existing cancer treatment methods. This review summarizes the research progress made into NOB1 in cancer in the past decade; this information provides valuable clues and theoretical guidance for future anticancer therapy by targeting NOB1.

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