A radiation resistance related index for biochemical recurrence and tumor immune environment in prostate cancer patients

Ke, Zhi‐Bin; You, Qi; Chen, Jia-Yin; Sun, Jiang-Bo; Xue, Yu-Ting; Zhuang, Rui-Bin; Zheng, Qing‐Shui; Chen, Ye‐Hui; Wei, Yong; Sun, Xiong‐Lin; Xue, Xue-Yi; Xu, Ning

doi:10.1016/j.compbiomed.2022.105711

Cited by 7 publications

(10 citation statements)

References 31 publications

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“…According to the projections provided by Alliance of Genome Resources, ZNF695 may enable DNAbinding transcription factor activity, RNA polymerase II-specific and RNA polymerase II cis-regulatory region sequence-specific DNA binding activity, and is predicted to be involved in regulation of transcription (https://www.alliancegenome.org/ gene/HGNC:30954#summary). Ke ZB et al found that ZNF695 is an important marker of radiotherapy resistance in prostate cancer (42), and is closely related to the proliferation, invasion and migration of prostate cancer cells, which may be an important factor affecting the microenvironment of prostate cancer (42,43).Takahashi T et al found that methylation of ZNF695 is an important factor affecting the chemotherapeutic resistance of esophageal squamous cell carcinoma (44). Some studies have also found that ZNF695 is closely related to the prognosis of breast cancer (45) and ovarian cancer (46).…”

Section: Discussionmentioning

confidence: 99%

“…Ke ZB et al. found that ZNF695 is an important marker of radiotherapy resistance in prostate cancer ( 42 ), and is closely related to the proliferation, invasion and migration of prostate cancer cells, which may be an important factor affecting the microenvironment of prostate cancer ( 42 , 43 ).Takahashi T et al. found that methylation of ZNF695 is an important factor affecting the chemotherapeutic resistance of esophageal squamous cell carcinoma ( 44 ).…”

Section: Discussionmentioning

confidence: 99%

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Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm

Chen

Sun²,

Chen³

et al. 2022

Front. Immunol.

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BackgroundThe prognosis of MYCN positive NB is poor, and there is no targeted drug for N-myc at present. This study aims to screen out hub genes closely related to MYCN, analyze the relationship between hub genes and NB microenvironment, and provide basis for molecular targeted therapy of MYCN positive NB.MethodsWe combined the microarray data of GSE45547 (n=649) and GSE49710 (n=498), screened the DEGs between MYCN positive (n=185) and MYCN negative NB (n=951), performed WGCNA, Lasso regression and Roc analyses on the merged matrix, and obtained the hub genes related to MYCN in the training group. We performed ssGSEA on the experimental group to calculate the infiltration level of 28 kinds of immune cells in each sample, compared the differences of immune cell infiltration between MYCN positive and MYCN negative group. The influences of hub genes on the distribution of each immune cell were also analyzed by ssGSEA. The expression differences of the three hub genes were verified in the E-MTAB-8248 cohort (n=223), and the correlation between hub genes and prognosis of NB was calculated by Kaplan-Meier method in GSE62564 (n=498) and the validation group. We also verified the expression differences of hub genes by qRT-PCR in SK-N-BE(2), SKNDZ, Kelly and SH-SY5Y cell lines.ResultsHere were 880 DEGs including 420 upregulated and 460 downregulated genes in MYCN positive NB in the training group. Overlap of the DEGs and WGCNA networks identified four shared genes, namely, ZNF695, CHEK1, C15ORF42 and EXO1, as candidate hub genes in MYCN positive NB. Three core genes, ZNF695, CHEK1 and C15ORF42, were finally identified by Lasso regression and Roc analyses. ZNF695, CHEK1 and C15ORF42 were highly expressed in MYCN positive NB tissues and cell lines. These three genes were closely related to the prognosis of children with NB. Except that Activated CD4 T cell and Type2 T helper cell increased, the infiltration levels of the other 26 cells decreased significantly in MYCN positive NB tissues. The infiltration levels of Type2 T helper cell and Activated CD4 T cell were also significantly positively correlated with the expression levels of the three hub genes.ConclusionZNF695, CHEK1 and C15ORF42 are highly expressed in MYCN positive NB, and their expression levels are negatively correlated with the prognosis of children with NB. The infiltration levels of Activated CD4 T cell and Type2 T helper cell increased in the microenvironment of MYCN positive NB and were significantly positively correlated with the expression levels of the three hub genes. The results of this study provide that ZNF695, CHEK1 and C15ORF42 may be potential prognostic markers and immunotherapy targets for MYCN positive NB.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm

Chen

Sun²,

Chen³

et al. 2022

Front. Immunol.

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“…According to Eschrich et al [6], the lower quartile of RSI was pre-de ned as the cut-off point for dividing patients into the RS and RR groups. The calculating formula of RRRI [9]…”

Section: Validation Of the Two Existing Radiosensitivity Signaturesmentioning

confidence: 99%

“…The 31-GS is developed by Kim's group, NCI-60 cancer cell panel (including prostate cancer) was analyzed for genes whose expression correlates with SF2 [8]. The RRRI is developed by Ke et al [9], and has been validated through TCGA and GSE cohort for its good biochemical recurrence predicting ability. Notably, there are no overlapping genes between the two radiosensitivity predictive indexes.…”

Section: Introductionmentioning

confidence: 99%

Integrating Radiosensitivity Gene Signature Improves Prostate Cancer Outcome Prediction

Wu,

Zheng,

Jiang

et al. 2023

Preprint

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Background This study aimed to establish a nomogram that combine 31-gene signature (31-GS), radiosensitivity index (RSI) and radiation resistance related gene index (RRRI) for predicting recurrence and in prostate cancer (PCa) patients.Methods The transcriptome data of PCa were obtained from GEO and TCGA to validate the predictive potential of three sets of published biomarkers, the 31-GS, RSI and RRRI. To adjust these markers for the characteristics of prostate cancer, we integrated four new PCa-associated radiosensitivity predictive indexes based on 31-GS, RSI and RRRI by the Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. A time-dependent receiver operating characteristic (ROC) curve, decision curve analyses (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were used to compare the radiosensitivity predictive ability of these four gene signatures. a nomogram was built to improve the recurrence prediction capability.Results We validated and compared the predictive potential of two published predictive indexes. Based on the 31-GS, RSI and RRRI, we integrated four PCa-associated radiosensitivity predictive indexes: 14Genes, RSI, RRRI, 20Genes. Among them, a 14-gene radiosensitivity predictive index showed the most promising predictive performance and discriminative capacity. The area under receiver operating characteristic curve for 14-gene is the highest in both TCGA and GSE cohort.Conclusions This study successfully established a Radiosensitivity related nomogram which had an excellent performance in predicting recurrence in patients with PCa. For patient who received radiation therapy, 20Genes and RRRI model can be used in predicting RFS while 20Genes is more radiotherapy-specific but needs further external validation.

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“…Currently, the recommended management method for BCR by European Association of Urology is mainly based on prostate-specific antigen doubling time (PSA-DT), Gleason score, International Society of Urological Pathology (ISUP) grade and interval from primary therapy to biochemical failure [ 15 ], but there are still defects in the process of clinical application. With the advent of next-generation sequencing, more and more biomarkers for the management of BCR based on transcriptomic data are identified from different perspectives [ 8 , 12 , 14 , 20 – 22 ]. Interestingly, radiomics attracts clinicians’ attention in PCa, such as prostate volume and other traits [ 23 , 24 ].…”

Section: Introductionmentioning

confidence: 99%

Membrane tension-mediated stiff and soft tumor subtypes closely associated with prognosis for prostate cancer patients

Wang

Shi

et al. 2023

Eur J Med Res

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Background Prostate cancer (PCa) is usually considered as cold tumor. Malignancy is associated with cell mechanic changes that contribute to extensive cell deformation required for metastatic dissemination. Thus, we established stiff and soft tumor subtypes for PCa patients from perspective of membrane tension. Methods Nonnegative matrix factorization algorithm was used to identify molecular subtypes. We completed analyses using software R 3.6.3 and its suitable packages. Results We constructed stiff and soft tumor subtypes using eight membrane tension-related genes through lasso regression and nonnegative matrix factorization analyses. We found that patients in stiff subtype were more prone to biochemical recurrence than those in soft subtype (HR 16.18; p < 0.001), which was externally validated in other three cohorts. The top ten mutation genes between stiff and soft subtypes were DNAH, NYNRIN, PTCHD4, WNK1, ARFGEF1, HRAS, ARHGEF2, MYOM1, ITGB6 and CPS1. E2F targets, base excision repair and notch signaling pathway were highly enriched in stiff subtype. Stiff subtype had significantly higher TMB and T cells follicular helper levels than soft subtype, as well as CTLA4, CD276, CD47 and TNFRSF25. Conclusions From the perspective of cell membrane tension, we found that stiff and soft tumor subtypes were closely associated with BCR-free survival for PCa patients, which might be important for the future research in the field of PCa.

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A radiation resistance related index for biochemical recurrence and tumor immune environment in prostate cancer patients

Cited by 7 publications

References 31 publications

Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm

Identification of hub genes and their correlation with infiltration of immune cells in MYCN positive neuroblastoma based on WGCNA and LASSO algorithm

Integrating Radiosensitivity Gene Signature Improves Prostate Cancer Outcome Prediction

Membrane tension-mediated stiff and soft tumor subtypes closely associated with prognosis for prostate cancer patients

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