Low expression of NCALD is associated with chemotherapy resistance and poor prognosis in epithelial ovarian cancer

Suppressed transcript diversity and immune response in COVID-19 ICU patients: a longitudinal study

Understanding the dynamic changes in gene expression during Acute Respiratory Distress Syndrome (ARDS) progression in post-acute infection patients is crucial for unraveling the underlying mechanisms. Study investigates the longitudinal changes in gene/transcript expression patterns in hospital-admitted severe COVID-19 patients with ARDS post-acute SARS-CoV-2 infection. Blood samples were collected at three time points and patients were stratified into severe and mild ARDS, based on their oxygenation saturation (SpO2/FiO2) kinetics over 7 d. Decline in transcript diversity was observed over time, particularly in patients with higher severity, indicating dysregulated transcriptional landscape. Comparing gene/transcript-level analyses highlighted a rather limited overlap. With disease progression, a transition towards an inflammatory state was evident. Strong association was found between antibody response and disease severity, characterized by decreased antibody response and activated B cell population in severe cases. Bayesian network analysis identified various factors associated with disease progression and severity, viz. humoral response, TLR signaling, inflammatory response, interferon response, and effector T cell abundance. The findings highlight dynamic gene/transcript expression changes during ARDS progression, impact on tissue oxygenation and elucidate disease pathogenesis.

A prognostic model for ovarian neoplasms established by an integrated analysis of 1580 transcriptomic profiles

Even after debulking surgery combined with chemotherapy or new adjuvant chemotherapy paired with internal surgery, the average year of disease free survival in advanced ovarian cancer was approximately 1.7 years1. The development of a molecular predictor of early recurrence would allow for the identification of ovarian cancer (OC) patients with high risk of relapse. The Ovarian Cancer Disease Free Survival Predictor (ODFSP), a predictive model constructed from a special set of 1580 OC tumors in which gene expression was assessed using both microarray and sequencing platforms, was created by our team. To construct gene expression barcodes that were resistant to biases caused by disparate profiling platforms and batch effects, we employed a meta-analysis methodology that was based on the binary gene pair technique. We demonstrate that ODFSP is a reliable single-sample predictor of early recurrence (1 year or less) using the largest pool of OC transcriptome data sets available to date. The ODFSP model showed significantly high prognostic value for binary recurrence prediction unaffected by clinicopathologic factors, with a meta-estimate of the area under the receiver operating curve of 0.64 (P  =  4.6E-05) and a D-index (robust hazard ratio) of 1.67 (P  =  9.2E-06), respectively. GO analysis of ODFSP's 2040 gene pairs (collapsed to 886 distinct genes) revealed the involvement in small molecular catabolic process, sulfur compound metabolic process, organic acid catabolic process, sulfur compound biosynthetic process, glycosaminoglycan metabolic process and aminometabolic process. Kyoto encyclopedia of genes and genomes pathway analysis of ODFSP's signature genes identified prominent pathways that included cAMP signaling pathway and FoxO signaling pathway. By identifying individuals who might benefit from a more aggressive treatment plan or enrolment in a clinical trial but who will not benefit from standard surgery or chemotherapy, ODFSP could help with treatment decisions.

Long non-coding RNA MIDEAS-AS1 inhibits growth and metastasis of triple-negative breast cancer via transcriptionally activating NCALD

BACKGROUND

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with higher aggressiveness and poorer outcomes. Recently, long non-coding RNAs (lncRNAs) have become the crucial gene regulators in the progression of human cancers. However, the function and underlying mechanisms of lncRNAs in TNBC remains unclear.

METHODS

Based on public databases and bioinformatics analyses, the low expression of lncRNA MIDEAS-AS1 in breast cancer tissues was detected and further validated in a cohort of TNBC tissues. The effects of MIDEAS-AS1 on proliferation, migration, invasion were determined by in vitro and in vivo experiments. RNA pull-down assay and RNA immunoprecipitation (RIP) assay were carried out to reveal the interaction between MIDEAS-AS1 and MATR3. Luciferase reporter assay, Chromatin immunoprecipitation (ChIP) and qRT-PCR were used to evaluate the regulatory effect of MIDEAS-AS1/MATR3 complex on NCALD.

RESULTS

LncRNA MIDEAS-AS1 was significantly downregulated in TNBC, which was correlated with poor overall survival (OS) and progression-free survival (PFS) in TNBC patients. MIDEAS-AS1 overexpression remarkably inhibited tumor growth and metastasis in vitro and in vivo. Mechanistically, MIDEAS-AS1 mainly located in the nucleus and interacted with the nuclear protein MATR3. Meanwhile, NCALD was selected as the downstream target, which was transcriptionally regulated by MIDEAS-AS1/MATR3 complex and further inactivated NF-κB signaling pathway. Furthermore, rescue experiment showed that the suppression of cell malignant phenotype caused by MIDEAS-AS1 overexpression could be reversed by inhibition of NCALD.

CONCLUSIONS

Collectively, our results demonstrate that MIDEAS-AS1 serves as a tumor-suppressor in TNBC through modulating MATR3/NCALD axis, and MIDEAS-AS1 may function as a prognostic biomarker for TNBC.

The role of DNA methylation in ovarian cancer chemoresistance: A narrative review

Background and Aims

Ovarian cancer (OC) is the most lethal gynecological cancer. In 2018, it was responsible for over 180,000 deaths worldwide. The high mortality rate is the culmination of a lack of early diagnosis and high rates of chemotherapy resistance, which is synonymous with disease recurrence. Over the last two decades, an increasingly significant role of epigenetic mechanisms, in particular DNA methylation, has emerged. This review will discuss several of the most significant genes whose hypo/hypermethylation profiles are associated with chemoresistance. Aside from functionally elucidating and evaluating these epimutations, this review will discuss recent trials of DNA methyltransferase inhibitors (DNMTi). Finally, we will propose future directions that could enhance the feasibility of utilizing these candidate epimutations as clinical biomarkers.

Methods

To perform this review, a comprehensive literature search based on our keywords was conducted across the online databases PubMed and Google Scholar for identifying relevant studies published up until August 2022.

Results

Epimutations affecting MLH1, MSH2, and Ras-association domain family 1 isoform A (DNA damage repair and apoptosis); ATP-binding cassette subfamily B member 1 and methylation-controlled J (drug export); secreted frizzled-related proteins (Wnt/β-catenin signaling), neurocalcin delta (calcium and G protein-coupled receptor signaling), and zinc finger protein 671 all have potential as biomarkers for chemoresistance. However, specific uncertainties relating to these epimutations include histotype-specific differences, intrinsic versus acquired chemoresistance, and the interplay with complete surgical debulking. DNMTi for chemoresistant OC patients has shown some promise; however, issues surrounding their efficacy and dose-limiting toxicities remain; a personalized approach is required to maximize their effectiveness.

Conclusion

Establishing a panel of aberrantly methylated chemoresistance-related genes to predict chemoresponsiveness and patients' suitability to DNMTi could significantly reduce OC recurrence, while improving DNMTi therapy viability. To achieve this, a large-scale prospective genome-wide DNA methylation profile study that spans different histotypes, includes paired samples (before and after chemotherapy), and integrates transcriptomic and methylomic analysis, is warranted.

SENP3 promotes tumor progression and is a novel prognostic biomarker in triple-negative breast cancer

Background

The clinical outcome of triple-negative breast cancer (TNBC) is poor. Finding more targets for the treatment of TNBC is an urgent need. SENPs are SUMO-specific proteins that play an important role in SUMO modification. Among several tumor types, SENPs have been identified as relevant biomarkers for progression and prognosis. The role of SENPs in TNBC is not yet clear.

Methods

The expression and prognosis of SENPs in TNBC were analyzed by TCGA and GEO data. SENP3 coexpression regulatory networks were determined by weighted gene coexpression network analysis (WGCNA). Least absolute shrinkage and selection operator (LASSO) and Cox univariate analyses were used to develop a risk signature based on genes associated with SENP3. A time-dependent receiver operating characteristic (ROC) analysis was employed to evaluate a risk signature's predictive accuracy and sensitivity. Moreover, a nomogram was constructed to facilitate clinical application.

Results

The prognostic and expression effects of SENP family genes were validated using the TCGA and GEO databases. SENP3 was found to be the only gene in the SENP family that was highly expressed and associated with an unfavorable prognosis in TNBC patients. Cell functional experiments showed that knockdown of SENP3 leads to growth, invasion, and migration inhibition of TNBC cells in vitro. By using WGCNA, 273 SENP3-related genes were identified. Finally, 11 SENP3-related genes were obtained from Cox univariate analysis and LASSO regression. Based on this, a prognostic risk prediction model was established. The risk signature of SENP3-related genes was verified as an independent prognostic marker for TNBC patients.

Conclusion

Among SENP family genes, we found that SENP3 was overexpressed in TNBC and associated with a worse prognosis. SENP3 knockdown can inhibit tumor proliferation, invasion, and migration. In TNBC patients, a risk signature based on the expression of 11 SENP3-related genes may improve prognosis prediction. The established risk markers may be promising prognostic biomarkers that can guide the individualized treatment of TNBC patients.

NCALD as a potential predictive biomarker for the efficacy of platinum-based chemotherapy in ovarian cancer

Aim: Since reliable response predictors to platinum-based chemotherapy in ovarian cancer (OC) are scarce, we characterize NCALD as a predictive biomarker. Materials & methods: NCALD mRNA (n = 100) and protein (n = 102) expression was analyzed in OC samples and associated with patient outcome. A stable OC cell line knockdown was generated and cellular response to platinum was explored. Results: High NCALD mRNA and protein expression was significantly associated with longer overall patient survival (p = 0.037/0.002). Knockdown experiments revealed a significant association between cisplatin sensitivity and NCALD expression. Conclusion: Low NCALD expression was associated with reduced sensitivity to platinum-based chemotherapy. NCALD may be a new biomarker candidate to identify patients who might benefit from platinum-based chemotherapy.

N6‑methyladenosine upregulates miR‑181d‑5p in exosomes derived from cancer‑associated fibroblasts to inhibit 5‑FU sensitivity by targeting NCALD in colorectal cancer

Resistance to 5‑Fluorouracil (5‑FU) is a frequent occurrence in patients with colorectal cancer (CRC). MicroRNAs (miRNAs) from cancer‑associated fibroblasts (CAFs)‑secreted exosomes have been associated with 5‑FU sensitivity. The potential molecular mechanism of CAFs‑exosomal miRNAs in CRC remains unclear. The aim of the present study was to elucidate the role of exosomal miRNAs in 5‑FU sensitivity in CRC. Exosomes derived from CAFs were extracted. Exosomal miR‑181d‑5p was identified as a miRNA associated with 5‑FU sensitivity. The putative function of exosomal miR‑181d‑5p was evaluated by ethynyl‑2‑deoxyuridine staining, flow cytometry, RNA immunoprecipitation, luciferase reporter assay, tumor xenograft formation, reverse transcription‑quantitative PCR and western blot analysis. Modification of miR‑181d‑5p by the RNA N6‑methyladenosine (m⁶A) methyltransferase like (METTL)3 was examined by m6A methylation analysis. The results indicated that m⁶A modification and METTL3 expression were upregulated in CRC patients. METTL3‑dependent m⁶A methylation promoted the miR‑181b‑5p process by DiGeorge Syndrome Critical Region 8 (DGCR8) in CAFs. CAFs‑derived exosomes inhibited 5‑FU sensitivity in CRC cells through the METTL3/miR‑181d‑5p axis. A mechanistic study revealed that miR‑181d‑5p directly targeted neurocalcin δ (NCALD) to inhibit the 5‑FU sensitivity of CRC cells. Patients with higher NCALD levels exhibited a higher survival rate. Taken together, METTL3‑dependent m⁶A methylation was upregulated in CRC to promote the processing of miR‑181d‑5p by DGCR8. This led to increased miR‑181d‑5p expression, which inhibited the 5‑FU sensitivity of CRC cells by targeting NCALD. The results of the present study provided novel insight into exosomal microRNAs in 5‑FU sensitivity in CRC cells. Furthermore, exosomal miR‑181d‑5p may represent a potential prognostic marker for CRC.

Research Progress in Prognostic Factors and Biomarkers of Ovarian Cancer

Ovarian cancer is a serious threat to women's health; its early diagnosis rate is low and prone to metastasis and recurrence. The current conventional treatment for ovarian cancer is a combination of platinum and paclitaxel chemotherapy based on surgery. The recurrence and progression of ovarian cancer with poor prognosis is a major challenge in treatment. With rapid advances in technology, understanding of the molecular pathways involved in ovarian cancer recurrence and progression has increased, biomarker-guided treatment options can greatly improve the prognosis of patients. This review systematically discusses and summarizes existing and new information on prognostic factors and biomarkers of ovarian cancer, which is expected to improve the clinical management of patients and lead to effective personalized treatment.