Transcript Profiling Distinguishes Complete Treatment Responders With Locally Advanced Cervical Cancer

Fernández‐Retana, Jorge; Lasa-Gonsebatt, Federico; López–Urrutia, Eduardo; Coronel-Martínez, Jaime; Leon, David Cantu De; Jacobo-Herrera, Nadia; Peralta‐Zaragoza, Oscar; Montiel, Delia Pérez; Reynoso-Noverón, Nancy; Vázquez-Romo, Rafael; Pérez‐Plasencia, Carlos

doi:10.1016/j.tranon.2015.01.003

Cited by 15 publications

(19 citation statements)

References 27 publications

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“…It is interesting that these factors are overexpressed specifically in the tumoral component. Also, clinical data of 85 patients, diagnosed with locally advanced cervical cancer submitted to standard treatment and followed for 5 years, were obtained as described in Fernandez-Retana et al [32]. We analyzed for the first time the relative mRNA expression for OCT4 , SOX2 , KLF4 , C-MYC , and NANOG in tumor and normal cells.…”

Section: Resultsmentioning

confidence: 99%

Genes Involved in the Transcriptional Regulation of Pluripotency Are Expressed in Malignant Tumors of the Uterine Cervix and Can Induce Tumorigenic Capacity in a Nontumorigenic Cell Line

Ruíz

Valencia-González

Pérez-Montiel

et al. 2019

Stem Cells International

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Transcription factors OCT4, SOX2, KLF4, C-MYC, and NANOG (OSKM-N) regulate pluripotency and stemness, and their ectopic expression reprograms human and murine fibroblasts that constitute the key of regenerative medicine. To determine their contribution to cell transformation, we analyzed the gene expression profiles of these transcription factors in cervical cancer samples and found that they are preferentially expressed in the tumor component. Also, cancer stem cell-enriched cultures grown as sphere cultures showed overexpression of OSKM-N genes. Importantly, we observed that lentiviral-mediated transduction of these factors confers, to a nontumorigenic immortalized human cell line, properties of cancer stem cells as the ability to form tumors in a mouse model. When we performed a meta-analysis using microarray data from cervical cancer biopsies and normal tissues, we found that the expression of OSKM-N and some target genes allowed separating tumor and normal tissues between samples, which enhanced the importance of OSKM-N in the tumorigenesis. Finally, we analyzed and compared both transcript and protein expression profiles of these factors within a cohort of patients with cervical cancer. To our knowledge, this is the first time that the expression of OSKM-N is described to induce one of the main characteristics of the cancer stem cell, the tumorigenicity. And, more importantly, its exogenous expression in a nontumorigenic cell line is sufficient to induce a tumorigenic phenotype; furthermore, the differential expression of this transcription factor distinguishes tumor tissue and normal tissue in cervical samples.

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Section: Resultsmentioning

confidence: 99%

Genes Involved in the Transcriptional Regulation of Pluripotency Are Expressed in Malignant Tumors of the Uterine Cervix and Can Induce Tumorigenic Capacity in a Nontumorigenic Cell Line

Ruíz

Valencia-González

Pérez-Montiel

et al. 2019

Stem Cells International

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“…Genomic heterogeneity affect treatment response in LACC. Different responders of neoadjuvant chemotherapy in LACC exhibit diverse genomic profile (29). Twenty-sevenpredictive gene signature has been identified to be qualified for distinguishing responders from non-responders in LACC patients treated with concurrent chemoradiotherapy (30).…”

Section: Discussionmentioning

confidence: 99%

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

et al. 2020

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Objective: To investigate whether pre-treatment CT-derived radiomic features could be applied for prediction of clinical response to neoadjuvant chemotherapy (NACT) in locally advanced cervical cancer (LACC).Patients and Methods: Two hundred and seventy-seven LACC patients treated with NACT followed by surgery/radiotherapy were included in this multi-institution retrospective study. One thousand and ninety-four radiomic features were extracted from venous contrast enhanced and non-enhanced CT imaging for each patient. Five combined methods of feature selection were used to reduce dimension of features. Radiomics signature was constructed by Random Forest (RF) method in a primary cohort of 221 patients. A combined model incorporating radiomics signature with clinical factors was developed using multivariable logistic regression. Prediction performance was then tested in a validation cohort of 56 patients.Results: Radiomics signature containing pre-and post-contrast imaging features can adequately distinguish chemotherapeutic responders from non-responders in both primary and validation cohorts [AUCs: 0.773 (95% CI, 0.701-0.845) and 0.816 (95% CI, 0.690-0.942), respectively] and remain relatively stable across centers. The combined model has a better predictive performance with an AUC of 0.803 (95% CI, 0.734-0.872) in the primary set and an AUC of 0.821 (95% CI, 0.697-0.946) in the validation set, compared to radiomics signature alone. Both models showed good discrimination, calibration.Conclusion: Newly developed radiomic model provided an easy-to-use predictor of chemotherapeutic response with improved predictive ability, which might facilitate optimal treatment strategies tailored for individual LACC patients.

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“…The raw microarray data of this study is publicly available at GEO database (Gene Expression Omnibus, http:// www.ncbi.nlm.nih.gov/geo/) with the accession number GSE56303. 18…”

Section: Rna Purification and Microarray Hybridizationmentioning

confidence: 99%

Gene signature based on degradome-related genes can predict distal metastasis in cervical cancer patients

et al. 2017

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Cervical cancer is one of the leading causes of death in women worldwide, which mainly affects developing countries. The patients who suffer a recurrence and/or progression disease have a higher risk of developing distal metastases. Proteases comprising the degradome given its ability to promote cell growth, migration, and invasion of tissues play an important role during tumor development and progression. In this study, we used high-density microarrays and quantitative reverse transcriptase polymerase chain reaction to evaluate the degradome profile and their inhibitors in 112 samples of patients diagnosed with locally advanced cervical cancer. Clinical follow-up was done during a period of 3 years. Using a correlation analysis between the response to treatment and the development of metastasis, we established a molecular signature comprising eight degradome-related genes (FAM111B, FAM111A, CFB, PSMB8, PSMB9, CASP7, PRSS16, and CD74) with the ability to discriminate patients at risk of distal metastases. In conclusion, present results show that molecular signature obtained from degradome genes can predict the possibility of metastasis in patients with locally advanced cervical cancer.

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Transcript Profiling Distinguishes Complete Treatment Responders With Locally Advanced Cervical Cancer

Cited by 15 publications

References 27 publications

Genes Involved in the Transcriptional Regulation of Pluripotency Are Expressed in Malignant Tumors of the Uterine Cervix and Can Induce Tumorigenic Capacity in a Nontumorigenic Cell Line

Genes Involved in the Transcriptional Regulation of Pluripotency Are Expressed in Malignant Tumors of the Uterine Cervix and Can Induce Tumorigenic Capacity in a Nontumorigenic Cell Line

Prediction of Response to Preoperative Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer Using Multicenter CT-Based Radiomic Analysis

Gene signature based on degradome-related genes can predict distal metastasis in cervical cancer patients

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