bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2021‒12‒12
six papers selected by
Sergio Marchini
Humanitas Research

  1. Cancers (Basel). 2021 Nov 29. pii: 5993. [Epub ahead of print]13(23):
      High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an important area of research, as the major obstacle to the treatment of HGSOC is the development of resistance to platinum chemotherapy. The cause of chemoresistance is still largely unknown and may be due to epigenetics modifications that are driving HGSOC metastasis and treatment resistance. The identification of epigenetic changes in chemoresistant HGSOC enables the development of epigenetic modulating drugs that may be used to improve outcomes. Several epigenetic modulating drugs have displayed promise as drug targets for HGSOC, such as demethylating agents azacitidine and decitabine. Others, such as histone deacetylase inhibitors and miRNA-targeting therapies, demonstrated promising preclinical results but resulted in off-target side effects in clinical trials. This article reviews the epigenetic modifications identified in chemoresistant HGSOC and clinical trials utilizing epigenetic therapies in HGSOC.
    Keywords:  DNA methylation; DNA methyltransferase inhibitors; chemoresistance; epigenetic modifications; high-grade serous ovarian cancer; histone acetylation; histone deacetylase inhibitors; microRNA
  2. Cancers (Basel). 2021 Dec 04. pii: 6120. [Epub ahead of print]13(23):
      Ovarian cancer has the worst prognosis among gynecological cancers. In particular, clear cell and mucinous carcinomas are less sensitive to chemotherapy. The establishment of new therapies is necessary to improve the treatment outcomes for these carcinomas. In previous clinical studies, chemotherapy with cytotoxic anticancer drugs has failed to demonstrate better treatment outcomes than paclitaxel + carboplatin therapy. In recent years, attention has been focused on treatment with molecular target drugs and immune checkpoint inhibitors that target newly identified biomarkers. The issues that need to be addressed include the most appropriate combination of therapies, identifying patients who may benefit from each therapy, and how results should be incorporated into the standard of care for ovarian clear cell and mucinous carcinomas. In this article, we have reviewed the most promising therapies for ovarian clear cell and mucinous carcinomas, which are regarded as intractable, with an emphasis on therapies currently being investigated in clinical studies.
    Keywords:  chemotherapy; clear cell carcinoma; clinical trial; mucinous carcinoma; ovarian cancer
  3. Cancers (Basel). 2021 Dec 01. pii: 6063. [Epub ahead of print]13(23):
      Ovarian cancer is one of the most fatal cancers in women worldwide. Cytoreductive surgery combined with platinum-based chemotherapy has been the current first-line treatment standard. Nevertheless, ovarian cancer appears to have a high recurrence rate and mortality. Immunological processes play a significant role in tumorigenesis. The production of ligands for checkpoint receptors can be a very effective, and undesirable, immunosuppressive mechanism for cancers. The CTLA-4 protein, as well as the PD-1 receptor and its PD-L1 ligand, are among the better-known components of the control points. The aim of this paper was to review current research on immunotherapy in the treatment of ovarian cancer. The authors specifically considered immune checkpoints molecules such as PD-1/PDL-1 as targets for immunotherapy. We found that immune checkpoint-inhibitor therapy does not have an improved prognosis in ovarian cancer; although early trials showed that a combination of anti-PD-1/PD-L1 therapy with targeted therapy might have the potential to improve responses and outcomes in selected patients. However, we must wait for the final results of the trials. It seems important to identify a group of patients who could benefit significantly from treatment with immune checkpoints inhibitors. However, despite numerous trials, ICIs have not become part of routine clinical practice for the treatment of ovarian cancer.
    Keywords:  PD-1; PDL-1; checkpoint inhibitor; immune checkpoint; immunotherapy; ovarian cancer
  4. Front Immunol. 2021 ;12 763791
      Ovarian cancer (OC) is a devastating malignancy with a poor prognosis. The complex tumor immune microenvironment results in only a small number of patients benefiting from immunotherapy. To explore the different factors that lead to immune invasion and determine prognosis and response to immune checkpoint inhibitors (ICIs), we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify key prognostic IRGs. Patients were divided into high-risk and low-risk groups according to their immune and stromal scores. We used a bioinformatics method to identify four key IRGs that had differences in expression between the two groups and affected prognosis. We evaluated the sensitivity of treatment from three aspects, namely chemotherapy, targeted inhibitors (TIs), and immunotherapy, to evaluate the value of prediction models and key prognostic IRGs in the clinical treatment of OC. Univariate and multivariate Cox regression analyses revealed that these four key IRGs were independent prognostic factors of overall survival in OC patients. In the high-risk group comprising four genes, macrophage M0 cells, macrophage M2 cells, and regulatory T cells, observed to be associated with poor overall survival in our study, were higher. The high-risk group had a high immunophenoscore, indicating a better response to ICIs. Taken together, we constructed a PRSM and identified four key prognostic IRGs for predicting survival and response to ICIs. Finally, the expression of these key genes in OC was evaluated using RT-qPCR. Thus, these genes provide a novel predictive biomarker for immunotherapy and immunomodulation.
    Keywords:  immune checkpoint inhibitors (ICI); immune-related genes (IRGs); ovarian cancer; prognosis; tumor immune microenvironment
  5. Brief Bioinform. 2021 Dec 07. pii: bbab475. [Epub ahead of print]
      Investigating differentially methylated regions (DMRs) presented in different tissues or cell types can help to reveal the mechanisms behind the tissue-specific gene expression. The identified tissue-/disease-specific DMRs also can be used as feature markers for spotting the tissues-of-origins of cell-free DNA (cfDNA) in noninvasive diagnosis. In recent years, many methods have been proposed to detect DMRs. However, due to the lack of benchmark DMRs, it is difficult for researchers to choose proper methods and select desirable DMR sets for downstream studies. The application of DMRs, used as feature markers, can be benefited by the longer length of DMRs containing more CpG sites when a threshold is given for the methylation differences of DMRs. According to this, two metrics ($Qn$ and $Ql$), in which the CpG numbers and lengths of DMRs with different methylation differences are weighted differently, are proposed in this paper to evaluate the DMR sets predicted by different methods on BS-seq data. DMR sets predicted by eight methods on both simulated datasets and real BS-seq datasets are evaluated by the proposed metrics, the benchmark-based metrics, and the enrichment analysis of biological data, including genomic features, transcription factors and histones. The rank correlation analysis shows that the $Qn$ and $Ql$ are highly correlated to the benchmark metrics for simulated datasets and the biological data enrichment analysis for real BS-seq data. Therefore, with no need for additional biological data, the proposed metrics can help researchers selecting a more suitable DMR set on a certain BS-seq dataset.
    Keywords:  BS-seq; differentially methylated regions; methylation difference; rank correlation analysis