TBX2 expression is associated with platinum-sensitivity of ovarian serous carcinoma

Role of Fyn expression in predicting the sensitivity to platinum‑based chemotherapy in patients with ovarian serous carcinoma

Ovarian serous carcinoma is a gynecological malignancy associated with a high mortality rate, which is commonly diagnosed in the first instance at a late stage and has a propensity to develop resistance to platinum-based chemotherapy. Identifying reliable biomarkers for platinum sensitivity is critical for improving patient outcomes. The present retrospective study included 64 patients with high-grade serous ovarian carcinoma (Federation of Gynecology and Obstetrics stages III or IV). Patients were classified as platinum-sensitive (no relapse within 6 months of the last platinum administration) or platinum-resistant (relapse within 6 months). Immunohistochemical analysis was performed to evaluate Fyn expression in tumor tissues, and Fyn knockdown experiments were performed using the OVSAHO ovarian cancer cell line to assess carboplatin sensitivity. Fyn expression was significantly higher in platinum-resistant patients compared with in platinum-sensitive patients (P<0.01). A weighted Fyn expression score was developed and a cutoff score of 6 was determined to predict platinum sensitivity with a specificity of 65.5% and a sensitivity of 62.9%. Patients with low Fyn expression (score ≤6) exhibited higher platinum sensitivity and longer overall survival (P<0.05). Multivariate analysis identified Fyn expression and postoperative residual tumor size as independent predictors of platinum sensitivity (P=0.033 and P=0.023, respectively). In vitro, Fyn knockdown significantly increased carboplatin sensitivity in ovarian cancer cells (P<0.05). Fyn, a member of the Src family of kinases, serves a crucial role in various cellular functions and has been implicated in chemotherapy resistance. The results demonstrated a notable association between Fyn expression and platinum sensitivity in ovarian serous carcinoma. The findings suggested that Fyn may serve as a predictive biomarker for response to platinum-based chemotherapy, offering the potential for more personalized treatment strategies. To the best of our knowledge, the present study is the first to establish an association between Fyn expression and platinum sensitivity in advanced ovarian serous carcinoma. Prospective studies with larger, multi-center cohorts and comprehensive biomarker analyses are recommended to validate and extend these results, ultimately improving therapeutic strategies and patient prognosis.

Predicting recurrence in intermediate‑ and high‑risk stage IB‑IIB cervical cancer treated with adjuvant cisplatin and paclitaxel chemotherapy post‑radical hysterectomy: The role of TBX2 expression

Cervical cancer remains a significant global health concern despite advances in prevention and treatment. Current management for intermediate- to high-risk stage IB-IIB cervical cancer post-radical hysterectomy involves irradiation or concurrent chemoradiation, although patients can exhibit several adverse events. Adjuvant chemotherapy has emerged as a promising alternative; however, its efficacy remains unclear. T-box (TBX)2 is a transcription factor that is involved in the regulation of cell cycle progression during cancer and embryonic development. Additionally, elevated expression of TBX2 is associated with resistance to DNA-damaging chemotherapeutic agents, such as cisplatin, carboplatin and doxorubicin. The aim of the present study was to investigate the relationship between TBX2 expression and recurrence in patients receiving adjuvant cisplatin and paclitaxel (TP) chemotherapy post-radical hysterectomy. Additionally, the impact of TBX2 knockdown on cisplatin sensitivity was assessed in vitro. A retrospective analysis was performed on 100 patients. Patients were categorized into two groups based on recurrence within 2 years of treatment initiation: The non-recurrent group (n=85) and the recurrent group (n=15). TBX2 expression was assessed immunohistochemically, and multiple logistic regression analysis was performed to identify predictors of recurrence. Additionally, the impact of small interfering RNA-mediated TBX2 knockdown on cervical cancer cell sensitivity to cisplatin was evaluated. TBX2 expression was significantly higher in the recurrent group compared with that in the non-recurrent group (P<0.01). Patients were stratified into low TBX2 expression (weighted score ≤8; n=80) and high TBX2 expression (weighted score ≥9; n=20) groups. The high TBX2 expression group exhibited a higher recurrence rate compared with the low expression group (P<0.01). Multivariate analysis identified TBX2 expression as an independent predictor of recurrence (P<0.01). Moreover, TBX2 knockdown significantly enhanced cervical cancer cell sensitivity to cisplatin in vitro (P<0.05). These findings highlight TBX2 expression as a potential predictive biomarker for recurrence amongst patients with intermediate- to high-risk stage IB-IIB cervical cancer receiving adjuvant TP chemotherapy post-radical hysterectomy.

Expression and prognosis analysis of TBX2 subfamily in human lung carcinoma

PURPOSE

Lung cancer has a high morbidity and mortality rate of all cancers worldwide. Therefore, there is an urgent need for reliable cancer markers for diagnosis and prognosis of patients with lung cancer.

METHODS

In this study, we used the bioinformatics database to compare the expression of the TBX2 subfamily at the transcriptional and protein levels in non-small cell lung cancer. Then, to confirm our bioinformatics analysis above, we used western bloting to determine the expression of TBX2, TBX3, TBX4 and TBX5 in human lung squamous carcinoma cell lines. Besides, low expression of TBX2 subfamily predicted a poor prognosis of patients with lung cancer. Finally, The methylation database was used to explore the relationship between the low expression of TBX2 subfamily and methylation of gene promoter region.

RESULTS

Our data showed a significant decrease of TBX2 subfamily expression in lung cancer tissues of several histological subtypes. Finally, the methylation of TBX2 subfamily members in the promoter region of NSCLC was significantly higher than that in normal tissues.

CONCLUSION

Our research provided sufficient evidence that TBX2 subfamily might play an inhibitory role in malignancy progression of lung cancer, which is promising to shed light on discovering a novel reliable cancer marker for prognosis of lung cancer patients.

Computational Tactics for Precision Cancer Network Biology

Network biology has garnered tremendous attention in understanding complex systems of cancer, because the mechanisms underlying cancer involve the perturbations in the specific function of molecular networks, rather than a disorder of a single gene. In this article, we review the various computational tactics for gene regulatory network analysis, focused especially on personalized anti-cancer therapy. This paper covers three major topics: (1) cell line's (or patient's) cancer characteristics specific gene regulatory network estimation, which enables us to reveal molecular interplays under varying conditions of cancer characteristics of cell lines (or patient); (2) computational approaches to interpret the multitudinous and massive networks; (3) network-based application to uncover molecular mechanisms of cancer and related marker identification. We expect that this review will help readers understand personalized computational network biology that plays a significant role in precision cancer medicine.

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

Growing evidence suggest that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. A 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score and cluster models were effective at accurately distinguishing the overall survival of SOC. Analysis of genomic alterations were used to elaborate on the association between the 17-TFs related prognostic signature and genomic aberrations. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. The potential immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups. The results indicated that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients. In conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.

SLC7A2 serves as a potential biomarker and therapeutic target for ovarian cancer

The solute carrier (SLC) family is the largest group of membrane transporters, but their functions in ovarian cancer (OV) remain unclear. We analyzed SLC family members with amino acids-transporting functions in OV. The mRNA expression levels and prognostic values of SLCs in OV were analyzed in the Gene Expression Profiling Interactive Analysis and Kaplan–Meier Plotter database. Solute carrier family 7 member 2 (SLC7A2), which showed differential expression and the most significant prognostic value, was selected for further analyses. The cBioPortal database, Gene Set Enrichment Analysis and Weighted Correlation Network Analysis were used to explore the potential functions and molecular mechanisms of SLC7A2 in OV. Validations in our own samples and in Gene Expression Omnibus datasets were conducted. Functional validation in OV cell lines was carried out. In total, 73 SLC family members were analyzed. Seven members were upregulated while 11 members were downregulated in OV and 15 members were protective factors for prognosis while 12 members were risk factors. SLC7A2 was downregulated in OV, and it was positively associated with prognosis. Knockdown of SLC7A2 promoted viability, invasion and migration of OV cells. These SLC family members and in particular SLC7A2 represented novel biomarkers for diagnosis and treatment for OV.

Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives

Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.