ANKRD22 promotes progression of non-small cell lung cancer through transcriptional up-regulation of E2F1

Yin, Jun; Fu, Wanyi; Dai, Lu; Jiang, Zeyong; Liao, Hongying; Chen, Wenbin; Pan, Lei; Zhao, Jian

doi:10.1038/s41598-017-04818-y

Cited by 55 publications

(56 citation statements)

References 35 publications

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“…High expression of SGLT1, which is encoded by SLC5A1, is associated with tumor development and poor prognosis in ovarian cancer [75]. In addition, ANKRD22 promotes progression of non-small-cell lung cancer [76]. However, higher ANKRD22 expression levels in prostate cancer are associated with longer DFS following radical prostatectomy [77].…”

Section: Discussionmentioning

confidence: 99%

Downstream Effectors of ILK in Cisplatin-Resistant Ovarian Cancer

Reyes-González

Quiñones-Díaz

Santana

et al. 2020

Cancers

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Despite good responses to first-line treatment with platinum-based combination chemotherapy, most ovarian cancer patients will relapse and eventually develop platinum-resistant disease with poor prognosis. Although reports suggest that integrin-linked kinase (ILK) is a potential target for ovarian cancer treatment, identification of ILK downstream effectors has not been fully explored. The purpose of this study was to investigate the molecular and biological effects of targeting ILK in cisplatin-resistant ovarian cancer. Western blot analysis showed that phosphorylation levels of ILK were higher in cisplatin-resistant compared with cisplatin-sensitive ovarian cancer cells. Further immunohistochemical analysis of ovarian cancer patient samples showed a significant increase in phosphorylated ILK levels in the tumor tissue when compared to normal ovarian epithelium. Targeting ILK by small-interfering RNA (siRNA) treatment reduced cisplatin-resistant cell growth and invasion ability, and increased apoptosis. Differential gene expression analysis by RNA sequencing (RNA-Seq) upon ILK-siRNA transfection followed by Ingenuity Pathway Analysis (IPA) and survival analysis using the Kaplan–Meier plotter database identified multiple target genes involved in cell growth, apoptosis, invasion, and metastasis, including several non-coding RNAs. Taken together, results from this study support ILK as an attractive target for ovarian cancer and provide potential ILK downstream effectors with prognostic and therapeutic value.

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Section: Discussionmentioning

confidence: 99%

Downstream Effectors of ILK in Cisplatin-Resistant Ovarian Cancer

Reyes-González

Quiñones-Díaz

Santana

et al. 2020

Cancers

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“…Typhi (Salerno‐Goncalves et al , ). C1QB and C1QC are well‐known subunits of the complement subcomponent C1q and, together with ANKRD22 [involved in cell cycle control (Yin et al , )], have previously been described as part of a signature able to distinguish active from latent TB (Kaforou et al , ). The function of the transcription factor RFX7 is largely unknown but has been found to be strongly up‐regulated during blood‐stage malaria, and its selection in our 7‐gene signature is therefore likely to be driving the classification of malaria cases.…”

Section: Discussionmentioning

confidence: 99%

“…While ALDH1A1 has not specifically been linked with responses to invasive bacterial infections, it is involved in gut-homing of TCs through expression of retinoic acid (Molotkov & Duester, 2003;Iwata et al, 2004), a phenotype we have observed following infection with S. Typhi (Salerno-Goncalves et al, 2017). C1QB and C1QC are well-known subunits of the complement subcomponent C1q and, together with ANKRD22 [involved in cell cycle control (Yin et al, 2017)], have previously been described as part of a signature able to distinguish active from latent TB (Kaforou et al, 2013a). The function of the transcription factor RFX7 is largely unknown but has been found to be strongly up-regulated during blood-stage malaria, and its selection in our 7-gene signature is therefore likely to be driving the classification of malaria cases.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases

et al. 2019

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Misdiagnosis of enteric fever is a major global health problem, resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine learning algorithm to host gene expression profiles, we identified a diagnostic signature, which could distinguish culture‐confirmed enteric fever cases from other febrile illnesses (area under receiver operating characteristic curve > 95%). Applying this signature to a culture‐negative suspected enteric fever cohort in Nepal identified a further 12.6% as likely true cases. Our analysis highlights the power of data‐driven approaches to identify host response patterns for the diagnosis of febrile illnesses. Expression signatures were validated using qPCR, highlighting their utility as PCR‐based diagnostics for use in endemic settings.

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“…44,45 While ALDH1A1 has not specifically been linked with responses to invasive bacterial infections, it is involved in gut-homing of TCs through expression of retinoic acid, 46,47 a phenotype we have observed following infection with S. Typhi. 26 C1QB and C1QC are well-known subunits of the complement subcomponent C1q and, together with ANKRD22 (involved in cell cycle control 48 ), have previously been described as part of a signature able to distinguish active from latent TB. 17 The function of the transcription factor RFX7 is largely unknown, but has been found to be strongly up-regulated during blood stage malaria and its selection in our 7-gene signature is therefore likely to be driving the classification of malaria cases.…”

Section: Discussionmentioning

confidence: 99%

Diagnostic host gene signature to accurately distinguish enteric fever from other febrile diseases

Blohmke

Müller

Gibani

et al. 2018

Preprint

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28Misdiagnosis of enteric fever is a major global health problem resulting in patient mismanagement, 29 antimicrobial misuse and inaccurate disease burden estimates. Applying a machine-learning algorithm 30 to host gene expression profiles, we identified a diagnostic signature which could accurately 31 distinguish culture-confirmed enteric fever cases from other febrile illnesses (AUROC>95%). 32Applying this signature to a culture-negative suspected enteric fever cohort in Nepal identified a 33 further 12.6% as likely true cases. Our analysis highlights the power of data-driven approaches to 34 identify host-response patterns for the diagnosis of febrile illnesses. Expression signatures were 35 validated using qPCR highlighting their utility as PCR-based diagnostic for use in endemic settings. 36. CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint . http://dx.doi.org/10.1101/327429 doi: bioRxiv preprint first posted online May. 21, 2018; 3 Enteric fever, a disease caused by systemic infection with S. enterica serovars Typhi or Paratyphi A, 37 accounts for 13.5 to 26.9 million illness episodes worldwide each year.1,2 In resource-limited tropical 38 settings these infections are endemic and the accurate diagnosis of patients presenting with 39 undifferentiated fever is challenging. 40Diagnostic tests for enteric fever rely on microbiological culture or detection of a serological response 41 to infection, and are often unavailable or insufficiently sensitive and specific.3 Blood culture remains 42 the reference standard against which new diagnostic tests are evaluated, and the sensitivity for this test 43 can reach 80% under optimal conditions 4 but low blood volumes and uncontrolled antibiotic use often 44 result in decreased sensitive in the field. New diagnostic approaches are urgently needed to enable the 45 accurate detection of enteric fever cases in endemic settings, to guide management of febrile patients, 46 appropriate use of antimicrobials, and to identify populations likely to benefit from vaccine 47 implementation. 48Most common tests used for acute infectious disease diagnosis employ methods to directly detect the 49 disease-causing pathogen, either by culture, antigen detection or amplification of genetic material by 50PCR. An alternative approach is to identify a set of human host immune responses, which together 51 may generate a specific pattern associated with individual infections or pathogens. With an increasing 52 quantity of molecular host response data being generated by high-throughput methods -including 53 whole blood gene expression profiling -differences in the activation status of the immune response 54 network during infection may be a tractable diagnostic approach. Recently small sets containing 2-3 55 genes have been described, the expression of which can accurately differentiate between viral or...

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ANKRD22 promotes progression of non-small cell lung cancer through transcriptional up-regulation of E2F1

Cited by 55 publications

References 35 publications

Downstream Effectors of ILK in Cisplatin-Resistant Ovarian Cancer

Downstream Effectors of ILK in Cisplatin-Resistant Ovarian Cancer

Diagnostic host gene signature for distinguishing enteric fever from other febrile diseases

Diagnostic host gene signature to accurately distinguish enteric fever from other febrile diseases

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