Genomic alterations in STK11 can predict clinical outcomes in cervical cancer patients

Hirose, Sou; Murakami, Naoya; Takahashi, Kazuaki; Kuno, Ikumi; Takayanagi, Daisuke; Asami, Yuka; Matsuda, Maiko; Shimada, Yôko; Yamano, Shotaro; Sunami, Kuniko; Yoshida, Keisuke; Honda, Takayuki; Nakahara, Tomomi; Watanabe, Tomoko; Komatsu, Masaaki; Hamamoto, Ryuji; Kato, Mayumi Kobayashi; Matsumoto, Koji; Okuma, Kae; Kuroda, Takafumi; Okamoto, Aikou; Itami, Jun; Kato, Tomoyasu; Shiraishi, Kouya; Yoshida, Hiroshi

doi:10.1016/j.ygyno.2019.10.022

Cited by 30 publications

(22 citation statements)

References 40 publications

(48 reference statements)

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“…The increasing CC morbidity is closely linked to human papillomavirus (HPV) infection, chronic cervical lesions, genetic modification, and many other factors. The currently known genetic alterations associated with CC involve the ErbB-3 (Di et al, 2015;Cancer Genome Atlas Research Network et al, 2017), epidermal growth factor receptor (EGFR) (Wei et al, 2018), Serine/Threonine Kinase 11 (STK11) (Hirose et al, 2020), transforming growth factorbeta receptor 2 (TGFBR2) (Cai et al, 2018), phosphatase and tensin homolog (PTEN) (Nero et al, 2019), etc. Nevertheless, the underlying mechanisms of CC carcinogenesis and progression still remain elusive so far.…”

Section: Introductionmentioning

confidence: 99%

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Shen

2021

Front. Cell Dev. Biol.

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Tumor microenvironment (TME) is emerging as an essential part of cervical cancer (CC) tumorigenesis and development, becoming a hotspot of research these years. However, comprehending the specific composition of TME is still facing enormous challenges, especially the immune and stromal components. In this study, we downloaded the RNA-seq profiles and somatic mutation data of 309 CC cases from The Cancer Genome Atlas (TCGA) database, which were analyzed by integrative bioinformatical methods. Initially, ESTIMATE computational method was employed to calculate the amount of immune and stromal components. Then, based on the high- and low-immunity cohorts, we recognized the differentially expressed genes (DEGs) as well as the differentially mutated genes (DMGs). Additionally, we conducted an intersection analysis of DEGs and DMGs, ultimately determining an immune-related prognostic signature, GTPase, IMAP Family Member 4 (GIMAP4). Moreover, sequential analyses demonstrated that GIMAP4 was a protective factor in CC, positively correlated with the overall survival (OS) and negatively with distant metastasis. Besides, we utilized the Gene Set Enrichment Analysis (GSEA) to explore the enrichment-pathways in high and low-expression cohorts of GIMAP4. The results indicated that the genes of the high-expression cohort had a high enrichment in immune-related biological processes and metabolic activities in the low one. Furthermore, CIBERSORT analysis was applied to evaluate the proportion of tumor-infiltrating immune cells (TICs), illustrating that several activated TICs were strongly associated with GIMAP4 expression, which suggested that GIMAP4 had the potential to be an indicator for the immune state in TME of CC. Hence, GIMAP4 contributed to predicting the CC patients’ clinical outcomes, such as survival rate, distant metastasis and immunotherapy response. Moreover, GIMAP4 could serve as a promising biomarker for TME remodeling, suggesting the possible underlying mechanisms of tumorigenesis and CC progression, which may provide different therapeutic perceptions of CC, and therefore improve treatment.

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Section: Introductionmentioning

confidence: 99%

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Shen

2021

Front. Cell Dev. Biol.

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“…Several studies have reported that cervical cancer patients with PIK3CA mutations are associated with worse prognosis than those without the mutation 17 – 19 . However, the results of some reports differ from these findings 16 , 20 , necessitating further discussion. In addition, most studies have focused on the association of single or multiple genetic mutations with prognosis using surgical specimens 9 , 17 , 19 – 21 ; there are only a few reports on targeted sequencing using biopsy specimens from inoperable advanced cervical cancer 22 .…”

Section: Introductionmentioning

confidence: 76%

TP53 mutants and non-HPV16/18 genotypes are poor prognostic factors for concurrent chemoradiotherapy in locally advanced cervical cancer

Kuno

Takayanagi²,

Asami³

et al. 2021

Sci Rep

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Targeted sequencing for somatic mutations across the hotspots of 50 cancer-related genes was performed using biopsy specimens to investigate whether clinicopathological factors and genomic alterations correlated with prognosis in locally advanced cervical cancer. Seventy patients diagnosed with International Federation of Obstetrics and Gynecology (FIGO) stage III to IVA cervical cancer underwent radiotherapy or concurrent chemoradiotherapy at the National Cancer Center Hospital between January 2008 and December 2017. Mutations were detected in 47 of 70 [67% of cases; frequency of genetic alterations was as follows: PIK3CA (51%), FBXW7 (10%), PTEN (7.1%), and TP53 (5.7%)]. The Cancer Genome Atlas (TCGA) datasets showed a similar distribution of somatic mutations, but PIK3CA mutation frequency was significantly higher in our cohort than in TCGA datasets (P = 0.028). Patients with TP53 mutation were significantly related to poor progression-free survival (PFS) (hazard ratio [HR] = 3.53, P = 0.042). Patients with tumor diameters > 70 mm were associated with poor prognosis (HR = 2.96, P = 0.0048). Patients with non-HPV16/18 genotypes had worse prognosis than those with HPV16/18 genotypes (HR = 2.15, P = 0.030). Hence, patients with locally advanced cervical cancer, TP53 mutation, large tumor diameter, and non-HPV16/18 genotype were independently correlated with poor PFS, despite concurrent chemoradiotherapy.

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“…Genome data were analyzed using the ABI PRISM 7900HT Sequence Detection Software CopyCaller v2.1 (Thermo Fisher Scientific) for copy number analysis. Copy number amplification was defined as the process resulting in the presence of > 8 copies, while copy number loss was defined as the process resulting in the presence of < 1.2 copies, as previously reported 17 .…”

Section: Methodsmentioning

confidence: 99%

Distribution of genetic alterations in high-risk early-stage cervical cancer patients treated with postoperative radiation therapy

Murakami

Asami

Yoshida

et al. 2021

Sci Rep

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Somatic genetic alteration analysis was performed for post-hysterectomy high-risk early-stage uterine cervical cancer patients who underwent post-operative radiation therapy. Post-operative radiation therapy was performed for patients with pathological features of pelvic lymph node metastasis, parametrium invasion, or positive vaginal margin, which corresponded to the post-operative high-risk category. DNA was extracted from paraffin-embedded surgical specimens, and 50 somatic hotspot genetic alternations were detected using Ion AmpliSeq Cancer Hotspot Panel. The existence of actionable mutation was assessed based on OncoKB evidence level > 3A. Between January 2008 and November 2019, 89 patients who underwent abdominal radical hysterectomy followed by post-operative radiation therapy were identified. The follow-up period for living patients was 82.3 months (range 9.3–153.9), and the 5-year relapse-free survival and overall survival rates were 72.6% and 85.9%, respectively. The most frequently detected somatic mutation was PIK3CA (26 [29.2%] patients); however, no prognostic somatic genetic alterations were identified. Actionable mutations were detected in 30 (33.7%) patients. Actionable mutations were detected in approximately one-third of patients, suggesting that precision medicine can be offered to patients with post-operative high-risk uterine cervical cancer in the near future.

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Genomic alterations in STK11 can predict clinical outcomes in cervical cancer patients

Cited by 30 publications

References 40 publications

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

Integrated Bioinformatical Analysis Identifies GIMAP4 as an Immune-Related Prognostic Biomarker Associated With Remodeling in Cervical Cancer Tumor Microenvironment

TP53 mutants and non-HPV16/18 genotypes are poor prognostic factors for concurrent chemoradiotherapy in locally advanced cervical cancer

Distribution of genetic alterations in high-risk early-stage cervical cancer patients treated with postoperative radiation therapy

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