&lt;p&gt;Expression and Prognostic Significance of BANF1 in Triple-Negative Breast Cancer&lt;/p&gt;

et al. 2021

Cancer Cell Int

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Background Hepatocellular carcinoma (HCC) has become a global health issue of wide concern due to its high prevalence and poor therapeutic efficacy. Both tumor doubling time (TDT) and immune status are closely related to the prognosis of HCC patients. However, the association between TDT-related genes (TDTRGs) and immune-related genes (IRGs) and the value of their combination in predicting the prognosis of HCC patients remains unclear. The current study aimed to discover reliable biomarkers for anticipating the future prognosis of HCC patients based on the relationship between TDTRGs and IRGs. Methods Tumor doubling time-related genes (TDTRGs) were acquired from GSE54236 by using Pearson correlation test and immune-related genes (IRGs) were available from ImmPort. Prognostic TDTRGs and IRGs in TCGA-LIHC dataset were determined to create a prognostic model by the LASSO-Cox regression and stepwise Cox regression analysis. International Cancer Genome Consortium (ICGC) and another cohort of individual clinical samples acted as external validations. Additionally, significant impacts of the signature on HCC immune microenvironment and reaction to immune checkpoint inhibitors were observed. Results Among the 68 overlapping genes identified as TDTRG and IRG, a total of 29 genes had significant prognostic relevance and were further selected by performing a LASSO-Cox regression model based on the minimum value of λ. Subsequently, a prognostic three-gene signature including HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1), C-type lectin domain family 1 member B (CLEC1B), and Collectin sub-family member 12 (COLEC12) was finally identified by stepwise Cox proportional modeling. The signature exhibited superior accuracy in forecasting the survival outcomes of HCC patients in TCGA, ICGC and the independent clinical cohorts. Patients in high-risk subgroup had significantly increased levels of immune checkpoint molecules including PD-L1, CD276, CTLA4, CXCR4, IL1A, PD-L2, TGFB1, OX40 and CD137, and are therefore more sensitive to immune checkpoint inhibitors (ICIs) treatment. Finally, we first found that overexpression of CLEC1B inhibited the proliferation and migration ability of HuH7 cells. Conclusions In summary, the prognostic signature based on TDTRGs and IRGs could effectively help clinicians classify HCC patients for prognosis prediction and individualized immunotherapies.

Section: Methodsmentioning

confidence: 99%

A novel tumor doubling time-related immune gene signature for prognosis prediction in hepatocellular carcinoma

et al. 2021

Cancer Cell Int

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“…Fresh frozen tumor tissues from previously collected HCC patients were selected as a small sample size clinical validation cohort [19] and the clinical characteristics of HCC patients were showed in Table S1. qRT-PCR was used to detect the mRNA levels of genes in the model [20]. After the relative mRNAs expression levels were normalized to β -ACTIN and log 2 transformed, patients were strati ed into two subgroups according to the above formula.…”

Section: Clinical Specimens and Quantitative Real-tme Pcr (Qrt-pcr) Analysismentioning

confidence: 99%

Identification of a Novel Prognostic Classifier for Platelet-related Genes Characteristics and Prognostic Significance of Aberrant Expression of PAFAH1B3 in Hepatocellular Carcinoma

2021

Preprint

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BackgroundComplex crosstalk between tumor cells and platelets is closely related to the development, relapse, and drug resistance of hepatocellular carcinoma (HCC). Therefore, an intensive analysis of the relationship between platelet-related genes and the effectiveness of immunotherapy is necessary for improving the poor prognosis of HCC patients. MethodsGenes associated with platelets in the GeneCards database were collected and were used to identified molecular subtypes using a non-negative matrix decomposition algorithm (NMF) and constructed a platelet-related genes-based prognostic stratification model by the LASSO-Cox regression and stepwise Cox regression analysis. The effect of this feature on the immune microenvironment of HCC and the response to immune checkpoint inhibitors was also explored.ResultsAfter identifying two molecular subtypes, we constructed a platelet-related genes-based prognostic stratification model that can be effectively used for immune checkpoint inhibitor (PD1, PD-L1, PD-L2, and CTLA4) efficacy and prognosis prediction in HCC patients, which was subsequently validated using patient samples from ICGC, GSE14520 and a small sample size clinical cohort. We also found downregulation of PAFAH1B3 remarkably inhibited the proliferation and migration ability of Hep3B cells. ConclusionsIn conclusion, we constructed a prognostic classifier based on platelet-related genes that could effectively classify HCC patients for prognostic prediction provide new light on the selection of optimal individualized antiplatelet therapy for HCC patients in future clinical practice.

“…The total RNA was extracted using TRIzol reagent from tissues and then reverse-transcribed using a PrimeScript RT Master Mix Synthesis Kit for mRNAs as we reported previously. 8 The relative expression levels of mRNAs were quantified using Maxima SYBR Green qRT-PCR Master Mix (2×) in a Real-Time PCR system. The expression level of β-ACTIN was used as endogenous controls, and the relative mRNA levels of PZP expression were determined using the delta Cycle threshold (Ct) method 9 and expressed as average ±SD.…”

Section: Clinical Datamentioning

confidence: 99%

<p>Prognostic Significance of Pregnancy Zone Protein and Its Correlation with Immune Infiltrates in Hepatocellular Carcinoma</p>

Kong

2020

CMAR

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Human pregnancy zone protein (PZP) is a pregnancy-related protein which is increased dramatically during pregnancy. However, the expression of PZP and its prognostic value, association with tumor-infiltrating immune cells (TIICs) in microenvironment and potential biological process in HCC were unclear. Methods: The PZP expression, clinicopathology analysis and its influence on survival were analyzed by GEPIA and HPA. Fifty-nine HCC samples and 30 corresponding noncancerous tissues were collected and retrospectively analyzed to verify the results of bioinformatics analysis. Further, TIMER and CIBERSORT were performed to identify the significantly alerted biological process and affections of PZP expression on the immune system in patients with HCC. Finally, IHC assay of CD4+ T cells and Treg cells was performed to confirm the results of immune infiltrates analysis by TIMER and CIBERSORT. Results: PZP expression was downregulated in HCC tissues and its low level was substantially correlated with poor prognosis in patients with HCC. TIMER analysis showed that PZP expression had a positive correlation with the levels of macrophage and neutrophil. Furthermore, CIBERSORT analysis showed that resting memory CD4 T cells were increased in high PZP expression group, while the results of Tregs were the opposite. Finally, the IHC results of CD4+ T cells and Treg cells showed that only Tregs were negatively associated with PZP expression. Conclusion: PZP was identified as a novel prognosis biomarker of HCC and might play a vital role in the regulation and recruitment of TIICs in HCC immune microenvironment.