bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2021‒06‒20
thirteen papers selected by
Lara Paracchini
Humanitas Research

  1. Lancet Oncol. 2021 Jun 15. pii: S1470-2045(21)00216-3. [Epub ahead of print]
      BACKGROUND: Most patients with ovarian cancer will relapse after receiving frontline platinum-based chemotherapy and eventually develop platinum-resistant or platinum-refractory disease. We report results of avelumab alone or avelumab plus pegylated liposomal doxorubicin (PLD) compared with PLD alone in patients with platinum-resistant or platinum-refractory ovarian cancer.METHODS: JAVELIN Ovarian 200 was an open-label, parallel-group, three-arm, randomised, phase 3 trial, done at 149 hospitals and cancer treatment centres in 24 countries. Eligible patients were aged 18 years or older with epithelial ovarian, fallopian tube, or peritoneal cancer (maximum of three previous lines for platinum-sensitive disease, none for platinum-resistant disease) and an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients were randomly assigned (1:1:1) via interactive response technology to avelumab (10 mg/kg intravenously every 2 weeks), avelumab plus PLD (40 mg/m2 intravenously every 4 weeks), or PLD and stratified by disease platinum status, number of previous anticancer regimens, and bulky disease. Primary endpoints were progression-free survival by blinded independent central review and overall survival in all randomly assigned patients, with the objective to show whether avelumab alone or avelumab plus PLD is superior to PLD. Safety was assessed in all patients who received at least one dose of study treatment. This trial is registered with, NCT02580058. The trial is no longer enrolling patients and this is the final analysis of both primary endpoints.
    FINDINGS: Between Jan 5, 2016, and May 16, 2017, 566 patients were enrolled and randomly assigned (combination n=188; PLD n=190, avelumab n=188). At data cutoff (Sept 19, 2018), median duration of follow-up for overall survival was 18·4 months (IQR 15·6-21·9) for the combination group, 17·4 months (15·2-21·3) for the PLD group, and 18·2 months (15·8-21·2) for the avelumab group. Median progression-free survival by blinded independent central review was 3·7 months (95% CI 3·3-5·1) in the combination group, 3·5 months (2·1-4·0) in the PLD group, and 1·9 months (1·8-1·9) in the avelumab group (combination vs PLD: stratified HR 0·78 [repeated 93·1% CI 0·59-1·24], one-sided p=0·030; avelumab vs PLD: 1·68 [1·32-2·60], one-sided p>0·99). Median overall survival was 15·7 months (95% CI 12·7-18·7) in the combination group, 13·1 months (11·8-15·5) in the PLD group, and 11·8 months (8·9-14·1) in the avelumab group (combination vs PLD: stratified HR 0·89 [repeated 88·85% CI 0·74-1·24], one-sided p=0·21; avelumab vs PLD: 1·14 [0·95-1·58], one-sided p=0·83]). The most common grade 3 or worse treatment-related adverse events were palmar-plantar erythrodysesthesia syndrome (18 [10%] in the combination group vs nine [5%] in the PLD group vs none in the avelumab group), rash (11 [6%] vs three [2%] vs none), fatigue (ten [5%] vs three [2%] vs none), stomatitis (ten [5%] vs five [3%] vs none), anaemia (six [3%] vs nine [5%] vs three [2%]), neutropenia (nine [5%] vs nine [5%] vs none), and neutrophil count decreased (eight [5%] vs seven [4%] vs none). Serious treatment-related adverse events occurred in 32 (18%) patients in the combination group, 19 (11%) in the PLD group, and 14 (7%) in the avelumab group. Treatment-related adverse events resulted in death in one patient each in the PLD group (sepsis) and avelumab group (intestinal obstruction).
    INTERPRETATION: Neither avelumab plus PLD nor avelumab alone significantly improved progression-free survival or overall survival versus PLD. These results provide insights for patient selection in future studies of immune checkpoint inhibitors in platinum-resistant or platinum-refractory ovarian cancer.
    FUNDING: Pfizer and Merck KGaA, Darmstadt, Germany.
  2. Radiol Imaging Cancer. 2021 Apr;3(4): e200157
      The radiologic appearance of locally advanced lung cancer may be linked to molecular changes of the disease during treatment, but characteristics of this phenomenon are poorly understood. Radiomics, liquid biopsy of cell-free DNA (cfDNA), and next-generation sequencing of circulating tumor DNA (ctDNA) encode tumor-specific radiogenomic expression patterns that can be probed to study this problem. Preliminary findings are reported from a radiogenomic analysis of CT imaging, cfDNA, and ctDNA in 24 patients (median age, 64 years; range, 49-74 years) with stage III lung cancer undergoing chemoradiation on a prospective pilot study (NCT00921739) between September 2009 and September 2014. Unsupervised clustering of radiomic signatures resulted in two clusters that were associated with ctDNA TP53 mutations (P = .03) and changes in cfDNA concentration after 2 weeks of chemoradiation (P = .02). The radiomic features dissimilarity (hazard ratio [HR] = 0.56; P = .05), joint entropy (HR = 0.56; P = .04), sum entropy (HR = 0.53; P = .02), and normalized inverse difference (HR = 1.77; P = .05) were associated with overall survival. These results suggest heterogeneous and low-attenuating disease without a detectable ctDNA TP53 mutation was associated with early surges of cfDNA concentration in response to therapy and a generally better prognosis. Keywords: CT-Quantitative, Radiation Therapy, Lung, Computer Applications-3D, Oncology, Tumor Response, Outcomes Analysis Clinical trial registration no. NCT00921739 Supplemental material is available for this article. © RSNA, 2021.
    Keywords:  CT-Quantitative; Computer Applications-3D; Lung; Oncology; Outcomes Analysis; Radiation Therapy; Tumor Response
  3. Front Oncol. 2021 ;11 683057
      Our hypothesis was that the predictive accuracy of pathogenic variants in genes participating in the homologous recombination repair (HRR) system in patients with epithelial ovarian cancer (EOC) could be improved by considering additional next-generation sequencing (NGS) metrics. NGS genotyping was performed in tumor tissue, retrospectively and prospectively collected from patients with EOC, diagnosed from 8/1998 to 10/2016. Variants were considered clonal when variant allele frequencies corresponded to >25%. The primary endpoint was overall survival (OS). This study included 501 patients with EOC, predominantly with high-grade serous (75.2%) and advanced stage tumors (81.7%); median age was 58 years (22-84). Pathogenic and clonal pathogenic variants in HRR and/or TP53 genes were identified in 72.8% and 66.5% tumors, respectively. With a median follow-up of 123.9 months, the presence of either pathogenic or clonal pathogenic HRR-only variants was associated with longer OS compared to HRR/TP53 co-mutation (HR=0.54; 95% CI, 0.34-0.87, Wald's p=0.012 and HR=0.45; 95% CI, 0.27-0.78, Wald's p=0.004, respectively). However, only the presence of clonal HRR-only variants was independently associated with improved OS (HR=0.55; 95% CI, 0.32-0.94, p=0.030). Variant clonality and co-occuring TP53 variants affect the predictive value of HRR pathogenic variants for platinum agents in patients with EOC.Clinical Trial Registration: [], identifier [NCT04716374].
    Keywords:  BRCA; biomarker; co-mutation; homologous recombination repair; predictive; prognostic
  4. Curr Oncol Rep. 2021 Jun 14. 23(8): 92
      PURPOSE OF REVIEW: We review the emerging evidence regarding the relationship between the microbiota of the gastrointestinal and female reproductive tracts and gynecologic cancer.RECENT FINDINGS: The microbiome has essential roles in maintaining health. In recent years, the microbiota of the gastrointestinal and female reproductive tracts have been linked to many diseases, including gynecologic cancer. Alterations to the bacterial populations in a microbiota, or dysbiosis, have been shown to favor a pro-carcinogenic state through altered immune responses, dysregulated hormone metabolism, and modulation of the cell cycle. Pre-clinical and clinical studies have emerged, demonstrating that specific bacteria or microbial communities may be associated with increased risk for uterine, ovarian, and cervical cancers. Notably, numerous studies have linked a non-Lactobacillus-dominant vaginal microbiota, composed of anaerobic bacteria, with HPV infection, persistence, and development of invasive cervical cancer. Similarly, next-generation high-throughput sequencing techniques have enabled the characterization of unique microbiotas in patients with malignant and benign gynecologic conditions, shedding light on new associations between bacterial species and gynecologic cancers. Harnessing the power of the microbiome for early diagnosis, therapeutic intervention and modulation creates tremendous potential to optimize gynecologic cancer outcomes in the future.
    Keywords:  Cervical cancer; Gut microbiome; Gynecologic cancer; Microbiome; Ovarian cancer; Uterine cancer; Vaginal microbiome
  5. Nature. 2021 Jun 16.
      Minimally invasive approaches to detect residual disease after surgery are needed to identify patients with cancer who are at risk for metastatic relapse. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease and relapse1. We evaluated outcomes in 581 patients who had undergone surgery and were evaluable for ctDNA from a randomized phase III trial of adjuvant atezolizumab versus observation in operable urothelial cancer. This trial did not reach its efficacy end point in the intention-to-treat population. Here we show that ctDNA testing at the start of therapy (cycle 1 day 1) identified 214 (37%) patients who were positive for ctDNA and who had poor prognosis (observation arm hazard ratio = 6.3 (95% confidence interval: 4.45-8.92); P < 0.0001). Notably, patients who were positive for ctDNA had improved disease-free survival and overall survival in the atezolizumab arm versus the observation arm (disease-free survival hazard ratio = 0.58 (95% confidence interval: 0.43-0.79); P = 0.0024, overall survival hazard ratio = 0.59 (95% confidence interval: 0.41-0.86)). No difference in disease-free survival or overall survival between treatment arms was noted for patients who were negative for ctDNA. The rate of ctDNA clearance at week 6 was higher in the atezolizumab arm (18%) than in the observation arm (4%) (P = 0.0204). Transcriptomic analysis of tumours from patients who were positive for ctDNA revealed higher expression levels of cell-cycle and keratin genes. For patients who were positive for ctDNA and who were treated with atezolizumab, non-relapse was associated with immune response signatures and basal-squamous gene features, whereas relapse was associated with angiogenesis and fibroblast TGFβ signatures. These data suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in patients who are positive for ctDNA and who are at a high risk of relapse. These findings, if validated in other settings, would shift approaches to postoperative cancer care.
  6. Nat Commun. 2021 06 17. 12(1): 3636
      To identify approaches to target DNA repair vulnerabilities in cancer, we discovered nanomolar potent, selective, low molecular weight (MW), allosteric inhibitors of the polymerase function of DNA polymerase Polθ, including ART558. ART558 inhibits the major Polθ-mediated DNA repair process, Theta-Mediated End Joining, without targeting Non-Homologous End Joining. In addition, ART558 elicits DNA damage and synthetic lethality in BRCA1- or BRCA2-mutant tumour cells and enhances the effects of a PARP inhibitor. Genetic perturbation screening revealed that defects in the 53BP1/Shieldin complex, which cause PARP inhibitor resistance, result in in vitro and in vivo sensitivity to small molecule Polθ polymerase inhibitors. Mechanistically, ART558 increases biomarkers of single-stranded DNA and synthetic lethality in 53BP1-defective cells whilst the inhibition of DNA nucleases that promote end-resection reversed these effects, implicating these in the synthetic lethal mechanism-of-action. Taken together, these observations describe a drug class that elicits BRCA-gene synthetic lethality and PARP inhibitor synergy, as well as targeting a biomarker-defined mechanism of PARPi-resistance.
  7. Epigenetics. 2021 Jun 15. 1-25
      Epigenome editing consists of fusing a predesigned DNA recognition unit to the catalytic domain of a chromatin modifying enzyme leading to the introduction or removal of an epigenetic mark at a specific locus. These platforms enabled the study of the mechanisms and roles of epigenetic changes in several research domains such as those addressing pathogenesis and progression of cancer. Despite the continued efforts required to overcome some limitations, which include specificity, off-target effects, efficacy, and longevity, these tools have been rapidly progressing and improving.Since prostate cancer is characterized by multiple genetic and epigenetic alterations that affect different signalling pathways, epigenetic editing constitutes a promising strategy to hamper cancer progression. Therefore, by modulating chromatin structure through epigenome editing, its conformation might be better understood and events that drive prostate carcinogenesis might be further unveiled.This review describes the different epigenome engineering tools, their mechanisms concerning gene's expression and regulation, highlighting the challenges and opportunities concerning prostate cancer research.
    Keywords:  Prostate cancer; crispr-dCas9; epigenome editing; fusion proteins
  8. Recent Pat Anticancer Drug Discov. 2021 Jun 15.
      BACKGROUND: N6-Methyladenosine (m6A) RNA methylation is the most universal mRNA modification in eukaryotic cells. M6A mRNA modification affects almost every phases of RNA processing, including splicing, decay, export, translation and expression. Several patents have reported the application of m6A mRNA modification in cancer diagnosis and treatment. Ovarian cancer is the leading cause of death among all gynecological cancers. It is urgent to identify new biomarkers for early diagnosis and prognosis of ovarian cancer.OBJECTIVE: In the current study, we aimed to evaluate the m6A RNA methylation regulators and m6A related genes and establish a new gene signature panel for prognosis of ovarian cancer.
    METHOD: We downloaded the Mutations data, FPKM data and corresponding clinical information of 373 patients with ovarian cancer (OC) from the TCGA database. We performed LASSO regression analysis and multivariate cox regression analysis to develop a risk-identifying gene signature panel.
    RESULTS: A total of 317 candidate m6A RNA methylation related genes were obtained. Finally, 12 -genes (WTAP, LGR6, ZC2HC1A, SLC4A8, AP2A1, NRAS, CUX1, HDAC1, CD79A, ACE2, FLG2 and LRFN1) were selected to establish the signature panel. We analyzed the genetic alterations of the selected 12 -genes in OC using cBioPortal database. Among the 373 patients, 368 patients have mutations. The results showed that all queried genes were altered in 137 of 368 cases (37.23%). The 12-gene signature panel was confirmed as an independent prognostic indicator (P =2.29E-18, HR = 1.699, 95% CI = 1.508-1.913).
    CONCLUSION: We established an effective m6A-related gene signature panel consisted of 12 -genes, which can predict the outcome of patients with OC. The high risk score indicates unfavorable survival. Our study provided novel insights into the relationship between m6A and OC. This gene signature panel will be helpful in identifying poor prognostic patients with OC and could be a promising prognostic indicator in clinical practice.
    Keywords:  N6-Methyladenosine; methylation; ovarian cancer; prognostic indicator; biomarkers; tumorigenesis
  9. Front Mol Biosci. 2021 ;8 683240
      Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and high mortality worldwide. DNA methylation, one of the most common epigenetic changes, might serve a vital regulatory role in cancer. Methods: To identify categories based on DNA methylation data, consensus clustering was employed. The risk signature was yielded by systematic bioinformatics analyses based on the remarkably methylated CpG sites of cluster 1. Kaplan-Meier analysis, variable regression analysis, and ROC curve analysis were further conducted to validate the prognosis predictive ability of risk signature. Gene set enrichment analysis (GSEA) was performed for functional annotation. To uncover the context of tumor immune microenvironment (TIME) of HCC, we employed the ssGSEA algorithm and CIBERSORT method and performed TIMER database exploration and single-cell RNA sequencing analysis. Additionally, quantitative real-time polymerase chain reaction was employed to determine the LRRC41 expression and preliminarily explore the latent role of LRRC41 in prognostic prediction. Finally, mutation data were analyzed by employing the "maftools" package to delineate the tumor mutation burden (TMB). Results: HCC samples were assigned into seven subtypes with different overall survival and methylation levels based on 5'-cytosine-phosphate-guanine-3' (CpG) sites. The risk prognostic signature including two candidate genes (LRRC41 and KIAA1429) exhibited robust prognostic predictive accuracy, which was validated in the external testing cohort. Then, the risk score was significantly correlated with the TIME and immune checkpoint blockade (ICB)-related genes. Besides, a prognostic nomogram based on the risk score and clinical stage presented powerful prognostic ability. Additionally, LRRC41 with prognostic value was corroborated to be closely associated with TIME characterization in both expression and methylation levels. Subsequently, the correlation regulatory network uncovered the potential targets of LRRC41 and KIAA1429. Finally, the methylation level of KIAA1429 was correlated with gene mutation status. Conclusion: In summary, this is the first to identify HCC samples into distinct clusters according to DNA methylation and yield the CpG-based prognostic signature and quantitative nomogram to precisely predict prognosis. And the pivotal player of DNA methylation of genes in the TIME and TMB status was explored, contributing to clinical decision-making and personalized prognosis monitoring of HCC.
    Keywords:  DNA methylation sites; hepatocellular carcinoma; immune checkpoint blockade; prognosis; tumor immune environment; tumor mutation burden
  10. Clin Cancer Res. 2021 Jun 15. pii: clincanres.0572.2021. [Epub ahead of print]
      PURPOSE: The role of circulating cell-free tumor DNA (ctDNA) as an adjunct to tissue genomic profiling is poorly defined in metastatic renal cell carcinoma (mRCC). In this study we aim to validate previous findings related to genomic alteration (GA) frequency in ctDNA and determine the concordance between ctDNA and tissue-based profiling in patients with mRCC.EXPERIMENTAL DESIGN: Results of 839 mRCC patients who had ctDNA assessment with a CLIA-certified ctDNA assay between November 2016 and December 2019 were collected. Tissue-based genomic profiling was collected when available and concordance analysis between blood- and tissue-based testing was performed.
    RESULTS: ctDNA was assessed in 839 patients (comprising 920 samples) with mRCC. GAs were detected in 661 samples (71.8%). Tissue-based GAs were assessed in 112 patients. Limiting our analyses to a common 73-/74-gene set and excluding samples with no ctDNA detected, a total of 228 mutations were found in tissue and blood. 34.7% (42/121) of the mutations identified in tissue were also identified via ctDNA, while 28.2% (42/149) of the mutations identified in liquid were also identified via tissue. Concordance between ctDNA and tissue-based profiling was inversely related to the time elapsed between these assays.
    CONCLUSIONS: This study confirms the feasibility of ctDNA profiling in the largest mRCC cohort to date, with ctDNA identifying multiple actionable alterations. It also demonstrates that ctDNA and tissue-based genomic profiling are complementary, with both platforms identifying unique alterations, and confirms that the frequency of unique alterations increases with greater temporal separation between tests.
  11. Expert Rev Anticancer Ther. 2021 Jun 15.
      INTRODUCTION: : The efficacy and safety of trabectedin/pegylated liposomal doxorubicin (trabectedin/PLD) in patients with recurrent ovarian cancer have been demonstrated in randomized clinical studies. Real-world evidence is a subsequent necessary step for completing information from clinical practice. In the case of trabectedin/PLD, this evidence derives from prospective studies, retrospective analyses, and case series.AREAS COVERED: : The present narrative review provides the most relevant data about efficacy and safety of trabectedin/PLD in real-world studies, and the interpretation of the experience with trabectedin/PLD in clinical practice for patients with recurrent ovarian cancer.
    EXPERT OPINION: : Trabectedin/PLD has a proven antitumor activity that is maintained when administered in advanced lines. Trabectedin/PLD in patients who have relapsed between 6 and 12 months have showed comparable survival outcomes than platinum-based regimens. Moreover, the administration of trabectedin/PLD was associated with a positive survival trend after two previous platinum lines and a significantly superior PFS after subsequent platinum-based therapy. Additionally, the activity of trabectedin seems to be increased in patients with BRCA-mutated ovarian cancer. Overall, real-word evidence has confirmed that trabectedin/PLD is an effective and safe non-platinum combination for advanced lines of chemotherapy in patients with platinum-sensitive recurrent ovarian cancer.
    Keywords:  Trabectedin; efficacy; ovarian cancer; real-world; safety
  12. Curr Oncol Rep. 2021 Jun 14. 23(8): 97
      PURPOSE OF REVIEW: Advanced epithelial ovarian cancer remains the most lethal gynaecological cancer. Most patients with advanced disease will relapse within 3 years after primary treatment with surgery and chemotherapy. Recurrences become increasing difficult to treat due to the emergence of drug resistance and 5-year survival has changed little over the last decade. Maintenance treatment, here defined as treatment given beyond primary chemotherapy, can both consolidate the response and prolong the control of disease which is an approach to improve survival.RECENT FINDINGS: Here we review maintenance strategies such as targeting angiogenesis, interference of DNA repair through inhibition of PARP, combinations of targeting agents, and immunotherapy and hormonal therapy. Much has been learnt from the success and challenges of these treatments that have in the last few years which led to significant reduction in disease recurrence, changed the guidelines for treatment, and established a new paradigm for the treatment of ovarian cancer.
    Keywords:  Antiangiogenic agents; Checkpoint inhibitors; Combined targeted therapies; Epithelial ovarian cancer; Fallopian tube cancer; Frontline maintenance treatment; Hormonal maintenance treatment; PARP inhibitors; Primary peritoneal cancer; Targeted therapies
  13. Ann Oncol. 2021 Jun 14. pii: S0923-7534(21)02055-X. [Epub ahead of print]
      BACKGROUND: Clinical management of soft tissue sarcoma (STS) is particularly challenging. Here, we used digital pathology and deep learning (DL) for diagnosis and prognosis prediction of STS.PATIENTS AND METHODS: Our retrospective, multi-center study included a total of 506 histopathological slides from 291 patients with STS. The TCGA cohort (240 patients) served as training and validation set. A second, multicenter cohort (51 patients) served as an additional test set. The use of the DL model as a clinical decision support system was evaluated by 9 pathologists with different levels of expertise. For prognosis prediction, 139 slides from 85 patients with leiomyosarcoma (LMS) were used. Area under the receiver operating characteristic (AUROC) and accuracy served as main outcome measures.
    RESULTS: The DL model achieved a mean AUROC of 0.97 (±0.01) and an accuracy of 79.9% (±6.1%) in diagnosing the five most common STS subtypes. The DL model significantly improved the accuracy of the pathologists from 46.3% (±15.5%) to 87.1% (±11.1%). Furthermore, they were significantly faster and more certain in their diagnosis. In leiomyosarcoma (LMS), the mean AUROC in predicting the disease-specific survival status was 0.91 (±0.1) and the accuracy was 88.9% (±9.9%). Cox regression showed the DL model's prediction to be a significant independent prognostic factor (p=0.008, HR 5.5, 95% CI 1.56-19.7) in these patients, outperforming other risk factors.
    CONCLUSION(S): DL can be used to accurately diagnose frequent subtypes of STS from conventional histopathological slides. It might be used for prognosis prediction in LMS, the most prevalent STS subtype in our cohort. It can also help pathologists to make faster and more accurate diagnoses. This could substantially improve the clinical management of STS patients.
    Keywords:  Artificial Intelligence; Clinical Decision Support System; Deep Learning; Digital Pathology; Prognosis Prediction; Soft Tissue Sarcoma