Hematoxylin and Eosin Staining Helps Reduce Maternal Contamination in Short Tandem Repeat Genotyping for Hydatidiform Mole Diagnosis.

Short tandem repeat (STR) genotyping provides parental origin information about aneuploidy pregnancy loss and has become the current gold standard for hydatidiform mole diagnosis. STR genotyping diagnostic support most commonly relies on formalin-fixed paraffin-embedded samples, but maternal contamination is one of the most common issues based on traditional unstained sections. To evaluate the influence of hematoxylin and eosin (H&E) staining on DNA quality and STR genotyping, DNA was isolated from unstained, deparaffinized hydrated, and H&E-stained tissue sections (i.e. 3 groups) from each of 6 formalin-fixed paraffin-embedded placentas. The macrodissected view field, DNA quality, and polymerase chain reaction amplification efficiency were compared among groups. STR genotyping analysis was performed in both the test cohort (n = 6) and the validation cohort (n = 149). H&E staining not only did not interfere with molecular DNA testing of formalin-fixed paraffin-embedded tissue but also had a clearer macrodissected field of vision. In the test cohort, H&E-stained sections were the only group that did not exhibit maternal miscellaneous peaks in STR genotyping results. In the validation cohort, 138 (92.62%) cases yielded satisfactory amplification results without maternal contamination. Thus, H&E staining helped to reduce maternal contamination in STR genotyping for hydatidiform mole diagnosis, suggesting that H&E-stained sections can be incorporated into the hydatidiform mole molecular diagnostic workflow.

Identification and validation of a seven cuproptosis-associated lncRNA signature to predict the prognosis of endometrial cancer.

OBJECTIVE: Endometrial cancer (EC) is one of the most prevalent cancers in women. Long non-coding RNAs (lncRNAs) are potential diagnostic biomarkers in patients with EC. METHODS: We obtained clinical information and transcriptome data for 552 patients with EC from The Cancer Genome Atlas database. Cuproptosis-associated lncRNAs were obtained through Pearson's correlation analysis. Univariate and multivariate Cox regression analyses were applied and a signature predicting overall survival (OS) among patients with EC was constructed. We also analyzed the tumor immune microenvironment and drug sensitivity. The results were validated by quantitative real time-polymerase chain reaction, and 5-ethynyl-2'-deoxyuridine and wound-healing assays. RESULTS: Seven cuproptosis-associated lncRNAs related to prognosis were screened out and a signature was constructed. OS was significantly superior in the low-risk group. In addition, patients in the low-risk group had more CD8+ T cell infiltration, a stronger type II interferon response, and greater cisplatin sensitivity. Expression levels of some of the lncRNAs were significantly increased by cuproptosis. Furthermore, silencing of lncRNA AC084117.1 significantly inhibited the proliferation and migration of EC cells. CONCLUSION: We constructed a seven cuproptosis-associated lncRNA signature to predict the prognosis of patients with EC with good predictive power.

Challenges in diagnosing hydatidiform moles: a review of promising molecular biomarkers.

INTRODUCTION: Hydatidiform moles (HMs) are pathologic conceptions with unique genetic bases and abnormal placental villous tissue. Overlapping ultrasonographical and histological manifestations of molar and non-molar (NM) gestations and HMs subtypes makes accurate diagnosis challenging. Currently, immunohistochemical analysis of p57 and molecular genotyping have greatly improved the diagnostic accuracy. AREAS COVERED: The differential expression of molecular biomarkers may be valuable for distinguishing among the subtypes of HMs and their mimics. Thus, biomarkers may be the key to refining HMs diagnosis. In this review, we summarize the current challenges in diagnosing HMs, and provide a critical overview of the recent literature about potential diagnostic biomarkers and their subclassifications. An online search on PubMed, Web of Science, and Google Scholar databases was conducted from the inception to 1 April 2022. EXPERT OPINION: The emerging biomarkers offer new possibilities to refine the diagnosis for HMs and pregnancy loss. Although the additional studies are required to be quantified and investigated in clinical trials to verify their diagnostic utility. It is important to explore, validate, and facilitate the wide adoption of newly developed biomarkers in the coming years.

Robust immune response stimulated by in situ injection of CpG/αOX40/cGAMP in αPD-1-resistant malignancy.

Recently, the emergence of immunotherapy has revolutionized traditional tumour treatment. However, effective treatments for patients exhibiting αPD-1 resistance are still lacking. In our study, a combination of cytosine-phosphate-guanine oligodeoxynucleotides (CpG-ODNs), anti-OX40 and cyclic guanosine monophosphate-adenosine monophosphate (cGAMP) injection in situ systematically generated a robust antitumour immune response in TC1 and B16 cells, which are αPD-1-resistant malignancies. More precisely, this method activates both adaptive and innate immunity. Additionally, in situ vaccination with CpG/αOX40/cGAMP fully activates the production of cytokines. However, the combination of αPD-1 does not improve the efficacy of triple therapy, prompting further questions. Collectively, the combination of CpG/αOX40/cGAMP causes the regression of various αPD-1-resistant tumours through the full mobilization of innate and adaptive immunity. In addition, we explored the therapeutic effect of triple therapy on the αPD-1-sensitive cell line CT26. The results showed that triple therapy could significantly enhance the therapeutic effect of αPD-1, and some mice even achieved complete tumour regression after the combined application of αPD-1 and triple treatment.

Anti-tumour effect of in situ vaccines combined with VEGFR inhibitors in the treatment of metastatic cervical cancer.

Cervical cancer is the fourth most common malignant tumor in the world, for advanced cervical cancer, more than 30% of patients continue to have tumor and relapse or metastasis after the traditional treatment (concurrent chemoradiotherapy), and the response rate of immune checkpoint inhibitor (PD-1) is less 15%, so additional approaches are required. In situ vaccine is a very promising immunotherapy strategy. In the preclinical study, the combination of CPG and anti-Ox40 antibody can completely resolve injection site tumours and distant tumours and leads to the recovery of most mice with lymphoma. However, our early exploration process found that the effect of CpG + OX40 in the treatment of advanced cervical cancer is not ideal. Hence, we explored the anti-tumor effect of CpG + OX40 combined with anti-angiogenic therapy for the first time. The results showed that the combination significantly inhibited the proliferation of primary and secondary tumor volume and prolonged the survival time of mice, compared with the control group, CD3+, CD4 + and CD8 + T cells in the combined group showed an increasing trend. In addition, in terms of metabolism, the anti-vascular effect of anlotinib can significantly reduce the blood supply and metabolic level of tumor, the expression of Ki67 and CD31 in the control group was significantly higher than that in each administration group. In conclusion, our preclinical research results showed that the combination of in situ vaccine and anti-angiogenic therapy has a good anti-tumor effect, and may potentially offer an effective treatment option for patients with advanced cervical cancer.

Identification of Tumor Microenvironment-Related Alternative Splicing Events to Predict the Prognosis of Endometrial Cancer.

BACKGROUND: Endometrial cancer (EC) is one of the most common female malignant tumors. The immunity is believed to be associated with EC patients' survival, and growing studies have shown that aberrant alternative splicing (AS) might contribute to the progression of cancers. METHODS: We downloaded the clinical information and mRNA expression profiles of 542 tumor tissues and 23 normal tissues from The Cancer Genome Atlas (TCGA) database. ESTIMATE algorithm was carried out on each EC sample, and the OS-related different expressed AS (DEAS) events were identified by comparing the high and low stromal/immune scores groups. Next, we constructed a risk score model to predict the prognosis of EC patients. Finally, we used unsupervised cluster analysis to compare the relationship between prognosis and tumor immune microenvironment. RESULTS: The prognostic risk score model was constructed based on 16 OS-related DEAS events finally identified, and then we found that compared with high-risk group the OS in the low-risk group was notably better. Furthermore, according to the results of unsupervised cluster analysis, we found that the better the prognosis, the higher the patient's ESTIMATE score and the higher the infiltration of immune cells. CONCLUSIONS: We used bioinformatics to construct a gene signature to predict the prognosis of patients with EC. The gene signature was combined with tumor microenvironment (TME) and AS events, which allowed a deeper understanding of the immune status of EC patients, and also provided new insights for clinical patients with EC.

Identification of prognostic alternative splicing events related to the immune microenvironment of hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, and its 5-year survival rate is less than 20%, despite various treatments being available. Increasing evidence indicates that alternative splicing (AS) plays a nonnegligible role in the formation and development of the tumor microenvironment (TME). However, the comprehensive analysis of the impact on prognostic AS events on immune-related perspectives in HCC is lacking but urgently needed. METHODS: The transcriptional data and clinical information of HCC patients were downloaded from TCGA (The Cancer Genome Atlas) database for calculating immune and stromal scores by ESTIMATE algorithm. We then divided patients into high/low score groups and explored their prognostic significance using Kaplan-Meier curves. Based on stromal and immune scores, differentially expressed AS events (DEASs) were screened and evaluated with functional enrichment analysis. Additionally, a risk score model was established by applying univariate and multivariate Cox regression analyses. Finally, gene set variation analysis (GSVA) was adopted to explore differences in biological behaviors between the high- and low-risk subgroups. RESULTS: A total of 370 HCC patients with complete and qualified corresponding data were included in the subsequent analysis. According to the results of ESTIMATE analysis, we observed that the high immune/stromal score group had a longer survival probability, which was significantly correlated with prognosis in HCC patients. In addition, 467 stromal/immune score-related DEASs were identified, and enrichment analysis revealed that DEASs were significantly enriched in pathways related to HCC tumorigenesis and the immune microenvironment. More importantly, the final prognostic signature containing 16 DEASs showed powerful predictive ability. Finally, GSVA demonstrated that activation of carcinogenic pathways and immune-related pathways in the high-risk group may lead to poor prognosis. CONCLUSIONS: Collectively, these outcomes revealed prognostic AS events related to carcinogenesis and the immune microenvironment, which may yield new directions for HCC immunotherapy.

Identification of EMT-Related Gene Signatures to Predict the Prognosis of Patients With Endometrial Cancer.

BACKGROUND: Endometrial cancer (EC) is one of the most common gynecological cancers. Epithelial-mesenchymal transition (EMT) is believed to be significantly associated with the malignant progression of tumors. However, there is no relevant study on the relationship between EMT-related gene (ERG) signatures and the prognosis of EC patients. METHODS: We extracted the mRNA expression profiles of 543 tumor and 23 normal tissues from The Cancer Genome Atlas database. Then, we selected differentially expressed ERGs (DEERGs) among these mRNAs. Next, univariate and multivariate Cox regression analyses were performed to select the ERGs with predictive ability for the prognosis of EC patients. In addition, risk score models were constructed based on the selected genes to predict patients' overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS). Finally, nomograms were constructed to estimate the OS and PFS of EC patients, and pan-cancer analysis was performed to further analyze the functions of a certain gene. RESULTS: Six OS-, ten PFS-, and five DFS-related ERGs were obtained. By constructing the prognostic risk score model, we found that the OS, PFS, and DFS of the high-risk group were notably poorer. Last, we found that AQP5 appeared in all three gene signatures, and through pan-cancer analysis, it was also found to play an important role in immunity in lower grade glioma (LGG), which may contribute to the poor prognosis of LGG patients. CONCLUSIONS: We constructed ERG signatures to predict the prognosis of EC patients using bioinformatics methods. Our findings provide a thorough understanding of the effect of EMT in patients with EC and provide new targets and ideas for individualized treatment, which has important clinical significance.

Construction and Validation of a Novel Glycometabolism-Related Gene Signature Predicting Survival in Patients With Ovarian Cancer.

Among all fatal gynecological malignant tumors, ovarian cancer has the highest mortality rate. The purpose of this study was to develop a stable and personalized glycometabolism-related prognostic signature to predict the overall survival of ovarian cancer patients. The gene expression profiles and clinical information of ovarian cancer patients were derived from four public GEO datasets, which were divided into training and testing cohorts. Glycometabolism-related genes significantly associated with prognosis were selected. A risk score model was established and validated to evaluate its predictive value. We found 5 genes significantly related to prognosis and established a five-mRNA signature. The five-mRNA signature significantly divided patients into a low-risk group and a high-risk group in the training set and validation set. Survival analysis showed that high risk scores obtained by the model were significantly correlated with adverse survival outcomes and could be regarded as an independent predictor for patients with ovarian cancer. In addition, the five-mRNA signature can predict the overall survival of ovarian cancer patients in different subgroups. In summary, we successfully constructed a model that can predict the prognosis of patients with ovarian cancer, which provides new insights into postoperative treatment strategies, promotes individualized therapy, and provides potential new targets for immunotherapy.

Identification and validation of a six-gene signature associated with glycolysis to predict the prognosis of patients with cervical cancer.

BACKGROUND: Cervical cancer (CC) is one of the most common gynaecological cancers. The gene signature is believed to be reliable for predicting cancer patient survival. However, there is no relevant study on the relationship between the glycolysis-related gene (GRG) signature and overall survival (OS) of patients with CC. METHODS: We extracted the mRNA expression profiles of 306 tumour and 13 normal tissues from the University of California Santa Cruz (UCSC) Database. Then, we screened out differentially expressed glycolysis-related genes (DEGRGs) among these mRNAs. All patients were randomly divided into training cohort and validation cohort according to the ratio of 7: 3. Next, univariate and multivariate Cox regression analyses were carried out to select the GRG with predictive ability for the prognosis of the training cohort. Additionally, risk score model was constructed and validated it in the validation cohort. RESULTS: Six mRNAs were obtained that were associated with patient survival. The filtered mRNAs were classified into the protective type (GOT1) and the risk type (HSPA5, ANGPTL4, PFKM, IER3 and PFKFB4). Additionally, by constructing the prognostic risk score model, we found that the OS of the high-risk group was notably poorer, which showed good predictive ability both in training cohort and validation cohort. And the six-gene signature is a prognostic indicator independent of clinicopathological features. Through the verification of PCR, the results showed that compared with the normal cervial tissuses, the expression level of six mRNAs were significantly higher in the CC tissue, which was consistent with our findings. CONCLUSIONS: We constructed a glycolysis-related six-gene signature to predict the prognosis of patients with CC using bioinformatics methods. We provide a thorough comprehension of the effect of glycolysis in patients with CC and provide new targets and ideas for individualized treatment.

Seven-Gene Signature Based on Glycolysis Is Closely Related to the Prognosis and Tumor Immune Infiltration of Patients With Gastric Cancer.

Background: Gastric cancer (GC) is one of the most common malignancies worldwide, exhibiting a high morbidity, and mortality. As the various treatment methods for gastric cancer are limited by disadvantages, many efforts to improve the efficacy of these treatments are being taken. Metabolic recombination is an important characteristic of cancer and has gradually caused a recent upsurge in research. However, systematic analysis of the interaction between glycolysis and GC patient prognosis and its potential associations with immune infiltration is lacking but urgently needed. Methods: We obtained the gene expression data and clinical materials of GC derived from The Cancer Genome Atlas (TCGA) dataset. Univariate and multivariate Cox proportional regression analyses were performed to select the optimal prognosis-related genes for subsequent modeling. We then validated our data in the GEO database and further verified the gene expression using the Oncomine database and PCR experiments. Besides, Gene set variation analysis (GSVA) analysis was employed to further explore the differences in activation status of biological pathways between the high and low risk groups. Furthermore, a nomogram was adopted to predict the individualized survival rate of GC patients. Finally, a violin plot and a TIMMER analysis were performed to analyse the characteristics of immune infiltration in the microenvironment. Results: A seven-gene signature, including STC1, CLDN9, EFNA3, ZBTB7A, NT5E, NUP50, and CXCR4, was established. Based on this seven-gene signature, the patients in the training set and testing sets could be divided into high-risk and low-risk groups. In addition, a nomogram based on risk and age showed good calibration and moderate discrimination. The results proved that the seven-gene signature had a strong capacity to predict the GC patient prognosis. Collectively, the violin plot and TIMMER analysis demonstrated that an immunosuppressive tumor microenvironment caused by hyperglycolysis led to poor prognosis. Conclusion: Taken together, these results established a genetic signature for gastric cancer based on glycolysis, which has reference significance for the in-depth study of the metabolic mechanism of gastric cancer and the exploration of new clinical treatment strategies.

Comprehensive analysis and establishment of a prediction model of alternative splicing events reveal the prognostic predictor and immune microenvironment signatures in triple negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is widely concerning because of high malignancy and poor prognosis. There is increasing evidence that alternative splicing (AS) plays an important role in the development of cancer and the formation of the tumour microenvironment. However, comprehensive analysis of AS signalling in TNBC is still lacking and urgently needed. METHODS: Transcriptome and clinical data of 169 TNBC tissues and 15 normal tissues were obtained and integrated from the cancer genome atlas (TCGA), and an overview of AS events was downloaded from the SpliceSeq database. Then, differential comparative analysis was performed to obtain cancer-associated AS events (CAAS). Metascape was used to perform parent gene enrichment analysis based on CAAS. Unsupervised cluster analysis was performed to analyse the characteristics of immune infiltration in the microenvironment. A splicing network was established based on the correlation between CAAS events and splicing factors (SFs). We then constructed prediction models and assessed the accuracy of these models by receiver operating characteristic (ROC) curve and Kaplan-Meier survival analyses. Furthermore, a nomogram was adopted to predict the individualized survival rate of TNBC patients. RESULTS: We identified 1194 cancer-associated AS events (CAAS) and evaluated the enrichment of 981 parent genes. The top 20 parent genes with significant differences were mostly related to cell adhesion, cell component connection and other pathways. Furthermore, immune-related pathways were also enriched. Unsupervised clustering analysis revealed the heterogeneity of the immune microenvironment in TNBC. The splicing network also suggested an obvious correlation between SFs expression and CAAS events in TNBC patients. Univariate and multivariate Cox regression analyses showed that the survival-related AS events were detected, including some significant participants in the carcinogenic process. A nomogram incorporating risk, AJCC and radiotherapy showed good calibration and moderate discrimination. CONCLUSION: Our study revealed AS events related to tumorigenesis and the immune microenvironment, elaborated the potential correlation between SFs and CAAS, established a prognostic model based on survival-related AS events, and created a nomogram to better predict the individual survival rate of TNBC patients, which improved our understanding of the relationship between AS events and TNBC.

Durable Response After Combination Of Concurrent Chemoradiotherapy And Anti-PD-1 Therapy In HER2-Negative Advanced Gastric Adenocarcinoma: A Case Report.

Advanced gastric cancer (AGC) is difficult to treat with poor prognosis. Despite various possible treatments, the median survival time of such patients remains unsatisfactory. Therefore, new therapeutic approaches or combinations need to be further explored. We herein reported a case of a 54-year-old male patient who was initially diagnosed with HER2-negative advanced gastric cancer. Based on previous studies and patient's desire, we made a therapeutic plan: the combination of concurrent radiochemotherapy and immune checkpoint blockade therapy. After about 4 months of combined therapy, the patient showed satisfactory complete response to tumor lesions even metastatic lesions (CR, disappearance of all target lesions). In summary, the combination of concurrent SOX regimen chemotherapy, stomach radiotherapy and PD-1 antibody immunotherapy is effective in the treatment of advanced gastric cancer.

Erastin Reverses ABCB1-Mediated Docetaxel Resistance in Ovarian Cancer.

Overexpression of drug efflux transport ABCB1 is correlated with multidrug resistance (MDR) among cancer cells. Upregulation of ABCB1 accounts for the recurrence of resistance to docetaxel therapy in ovarian cancer with poor survival. Erastin is a novel and specific small molecule that targets SLC7A11 to induce ferroptosis. In the present research, we explored the synergistic effect of erastin and docetaxel in ovarian cancer. We confirmed that the co-delivery of erastin with docetaxel significantly decreased cell viability, promoted cell apoptosis, and induced cell cycle arrest at G2/M in ovarian cancer cells with ABCB1 overexpression. Mechanistically, erastin dominantly elevated the intracellular ABCB1 substrate levels by restricting the drug-efflux activity of ABCB1 without alteration of the expression of ABCB1. Consequently, erastin can reverse ABCB1-mediated docetaxel resistance in ovarian cancer, revealing that the combination of erastin and docetaxel may potentially offer an effective administration for chemo-resistant patients suffering from ovarian cancers.