bims-ovdlit Biomed News
on Ovarian cancer: early diagnosis, liquid biopsy and therapy
Issue of 2022‒10‒16
nine papers selected by
Lara Paracchini
Humanitas Research

  1. Onco Targets Ther. 2022 ;15 1105-1117
      Poly(adenosine diphosphate-ribose) polymerase (PARP) inhibitors have revolutionised the management of patients with high-grade serous and endometrioid ovarian cancer demonstrating significant improvements in progression-free survival. Whilst the greatest benefit is seen with BRCA1/2 mutant cancers, it is clear that the benefit extends beyond this group. This sensitivity is thought to be due to homologous recombination deficiency (HRD), which is present in up to 50% of the high-grade serous cancers. Several different HRD assays exist, which fall into one of three main categories: homologous recombination repair (HRR)-related gene analysis, genomic "scars" and/or mutational signatures, and real-time HRD functional assessment. We review the emerging data on HRD as a predictive biomarker for PARP inhibitors and discuss the merits and disadvantages of different HRD assays.
    Keywords:  BRCA mutations; PARP inhibitors; homologous recombination deficiency; maintenance therapy; ovarian cancer
  2. Cells. 2022 Oct 03. pii: 3114. [Epub ahead of print]11(19):
      Research and advancing understanding of the tumor immune microenvironment (TIME) is vital to optimize and direct more effective cancer immune therapy. Pre-clinical bench research is vital to better understand the genomic interplay of the TIME and immune therapy responsiveness. However, a vital key to effective translational cancer research is having a bridge of translation to bring that understanding from the bench to the bedside. Without that bridge, research into the TIME will lack an efficient and effective translation into the clinic and cancer treatment decision making. As a clinical oncologist, the purpose of this commentary is to emphasize the importance of researching and improving clinical utility of the bridge, as well as the TIME research itself.
    Keywords:  liquid biopsy; tumor immune microenvironment
  3. Nat Rev Drug Discov. 2022 Oct 10.
      Mutations in the TP53 tumour suppressor gene are very frequent in cancer, and attempts to restore the functionality of p53 in tumours as a therapeutic strategy began decades ago. However, very few of these drug development programmes have reached late-stage clinical trials, and no p53-based therapeutics have been approved in the USA or Europe so far. This is probably because, as a nuclear transcription factor, p53 does not possess typical drug target features and has therefore long been considered undruggable. Nevertheless, several promising approaches towards p53-based therapy have emerged in recent years, including improved versions of earlier strategies and novel approaches to make undruggable targets druggable. Small molecules that can either protect p53 from its negative regulators or restore the functionality of mutant p53 proteins are gaining interest, and drugs tailored to specific types of p53 mutants are emerging. In parallel, there is renewed interest in gene therapy strategies and p53-based immunotherapy approaches. However, major concerns still remain to be addressed. This Review re-evaluates the efforts made towards targeting p53-dysfunctional cancers, and discusses the challenges encountered during clinical development.
  4. Front Oncol. 2022 ;12 995651
      Background: Malignant pleural mesothelioma (MPM) is a rare and intractable disease exhibiting a remarkable intratumoral heterogeneity and dismal prognosis. Although immunotherapy has reshaped the therapeutic strategies for MPM, patients react with discrepant responsiveness.Methods: Herein, we recruited 333 MPM patients from 5 various cohorts and developed an in-silico classification system using unsupervised Non-negative Matrix Factorization and Nearest Template Prediction algorithms. The genomic alterations, immune signatures, and patient outcomes were systemically analyzed across the external TCGA-MESO samples. Machine learning-based integrated methodology was applied to identify a gene classifier for clinical application.
    Results: The gene expression profiling-based classification algorithm identified immune-related subtypes for MPMs. In comparison with the non-immune subtype, we validated the existence of abundant immunocytes in the immune subtype. Immune-suppressed MPMs were enriched with stroma fraction, myeloid components, and immunosuppressive tumor-associated macrophages (TAMs) as well exhibited increased TGF-β signature that informs worse clinical outcomes and reduced efficacy of anti-PD-1 treatment. The immune-activated MPMs harbored the highest lymphocyte infiltration, growing TCR and BCR diversity, and presented the pan-cancer immune phenotype of IFN-γ dominant, which confers these tumors with better drug response when undergoing immune checkpoint inhibitor (ICI) treatment. Genetically, BAP1 mutation was most commonly found in patients of immune-activated MPMs and was associated with a favorable outcome in a subtype-specific pattern. Finally, a robust 12-gene classifier was generated to classify MPMs with high accuracy, holding promise value in predicting patient survival.
    Conclusions: We demonstrate that the novel classification system can be exploited to guide the identification of diverse immune subtypes, providing critical biological insights into the mechanisms driving tumor heterogeneity and responsible for cancer-related patient prognoses.
    Keywords:  immune subtypes; immunotherapy; machine learning-based gene classifier; malignant pleural mesothelioma; prognosis
  5. Clin Cancer Res. 2022 Oct 12. pii: CCR-22-1206. [Epub ahead of print]
    Nicola S Meagher, Kylie L Gorringe, Matthew J Wakefield, Adelyn Bolithon, Chi Nam Ignatius Pang, Derek S Chiu, Michael S Anglesio, Kylie-Ann Mallitt, Jennifer A Doherty, Holly R Harris, Joellen M Schildkraut, Andrew Berchuck, Kara L Cushing-Haugen, Ksenia Chezar, Angela Chou, Adeline Tan, Jennifer Alsop, Ellen Barlow, Matthias W Beckmann, Jessica Boros, David D Bowtell, Alison H Brand, James D Brenton, Ian Campbell, Dane Cheasley, Joshua Cohen, Cezary Cybulski, Esther Elishaev, Ramona Erber, Rhonda Farrell, Anna Fischer, Zhuxuan Fu, Blake Gilks, Anthony J Gill, Charlie Gourley, Marcel Grube, Paul Harnett, Arndt Hartmann, Anusha Hettiaratchi, Claus K Høgdall, Tomasz Huzarski, Anna Jakubowska, Mercedes Jimenez-Linan, Catherine J Kennedy, Byoung-Gie Kim, Jae-Weon Kim, Jae-Hoon Kim, Kayla Klett, Jennifer Koziak, Tiffany Lai, Angela Laslavic, Jenny Lester, Yee Leung, Na Li, Winston Liauw, Belle W X Lim, Anna Linder, Jan Lubinski, Sakshi Mahale, Constantina Mateoiu, Simone McInerny, Janusz Menkiszak, Parham Minoo, Suzana Mittelstadt, David Morris, Sandra Orsulic, Sang Yoon Park, Celeste Leigh Pearce, John V Pearson, Malcolm C Pike, Carmel M Quinn, Ganendra Raj Mohan, JianYu Rao, Marjorie J Riggan, Matthias Ruebner, Stuart Salfinger, Clare L Scott, Mitul Shah, Helen Steed, Colin J R Stewart, Deepak Subramanian, Soseul Sung, Katrina Tang, Paul Timpson, Robyn L Ward, Rebekka Wiedenhoefer, Heather Thorne, Paul A Cohen, Philip Crowe, Peter A Fasching, Jacek Gronwald, Nicholas J Hawkins, Estrid Høgdall, David G Huntsman, Paul A James, Beth Y Karlan, Linda E Kelemen, Stefan Kommoss, Gottfried E Konecny, Francesmary Modugno, Sue K Park, Annette Staebler, Karin Sundfeldt, Anna H Wu, Aline Talhouk, Paul D P Pharoah, Lyndal Anderson, Anna DeFazio, Martin Köbel, Michael L Friedlander, Susan J Ramus.
      PURPOSE: Advanced stage MOC have poor chemotherapy response and prognosis and lack biomarkers to aid Stage I adjuvant treatment. Differentiating primary mucinous ovarian carcinoma (MOC) from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathological and gene expression data were analysed to identify prognostic and diagnostic features.EXPERIMENTAL DESIGN: Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n=333), mucinous borderline ovarian tumors (MBOT, n=151), upper GI (n=65), and lower GI tumors (n=55).
    RESULTS: Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2-years from diagnosis, compared with expansile pattern in Stage I MOC (hazard ratio HR 2.77 (1.04-7.41, p=0.042). Increased expression of THBS2 and TAGLN were associated with shorter OS in MOC patients, (HR 1.25 (95% CI 1.04-1.51, p=0.016)) and (1.21 (1.01-1.45, p=0.043)) respectively. ERBB2 (HER2)-amplification or high mRNA expression was evident in 64/243 (26%) of MOCs, but only 8/243 (3%) were also infiltrative (4/39, 10%) or Stage III/IV (4/31, 13%).
    CONCLUSIONS: An infiltrative growth pattern infers poor prognosis within 2-years from diagnosis and may help select Stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confer an adverse prognosis and is upregulated in the infiltrative subtype which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies.
  6. Front Genet. 2022 ;13 983668
      Mosaicism-the existence of genetically distinct populations of cells in a particular organism-is an important cause of genetic disease. Mosaicism can appear as de novo DNA mutations, epigenetic alterations of DNA, and chromosomal abnormalities. Neurodevelopmental or neuropsychiatric diseases, including autism-often arise by de novo mutations that usually not present in either of the parents. De novo mutations might occur as early as in the parental germline, during embryonic, fetal development, and/or post-natally, through ageing and life. Mutation timing could lead to mutation burden of less than heterozygosity to approaching homozygosity. Developmental timing of somatic mutation attainment will affect the mutation load and distribution throughout the body. In this review, we discuss the timing of de novo mutations, spanning from mutations in the germ lineage (all ages), to post-zygotic, embryonic, fetal, and post-natal events, through aging to death. These factors can determine the tissue specific distribution and load of de novo mutations, which can affect disease. The disease threshold burden of somatic de novo mutations of a particular gene in any tissue will be important to define.
    Keywords:  autism spectrum disorder; de novo mutation; genetic diseases; germline mutation; mosaicism; repeat instability; somatic mutation; timing of mutation
  7. Int J Mol Sci. 2022 Oct 10. pii: 12041. [Epub ahead of print]23(19):
      Ovarian cancer is the deadliest gynecological cancer, leading to over 152,000 deaths each year. A late diagnosis is the primary factor causing a poor prognosis of ovarian cancer and often occurs due to a lack of specific symptoms and effective biomarkers for an early detection. Currently, cancer antigen 125 (CA125) is the most widely used biomarker for ovarian cancer detection, but this approach is limited by a low specificity. In recent years, multimarker panels have been developed by combining molecular biomarkers such as human epididymis secretory protein 4 (HE4), ultrasound results, or menopausal status to improve the diagnostic efficacy. The risk of ovarian malignancy algorithm (ROMA), the risk of malignancy index (RMI), and OVA1 assays have also been clinically used with improved sensitivity and specificity. Ongoing investigations into novel biomarkers such as autoantibodies, ctDNAs, miRNAs, and DNA methylation signatures continue to aim to provide earlier detection methods for ovarian cancer. This paper reviews recent advancements in molecular biomarkers for the early detection of ovarian cancer.
    Keywords:  CA125; HE4; RMI; ROMA; molecular biomarkers; ovarian cancer
  8. Sci Rep. 2022 Oct 09. 12(1): 16945
      Over the past decade, advances in genetic testing, particularly the advent of next-generation sequencing, have led to a paradigm shift in the diagnosis of molecular diseases and disorders. Despite our present collective ability to interrogate more than 90% of the human genome, portions of the genome have eluded us, resulting in stagnation of diagnostic yield with existing methodologies. Here we show how application of a new technology, long-read sequencing, has the potential to improve molecular diagnostic rates. Whole genome sequencing by long reads was able to cover 98% of next-generation sequencing dead zones, which are areas of the genome that are not interpretable by conventional industry-standard short-read sequencing. Through the ability of long-read sequencing to unambiguously call variants in these regions, we discovered an immunodeficiency due to a variant in IKBKG in a subject who had previously received a negative genome sequencing result. Additionally, we demonstrate the ability of long-read sequencing to detect small variants on par with short-read sequencing, its superior performance in identifying structural variants, and thirdly, its capacity to determine genomic methylation defects in native DNA. Though the latter technical abilities have been demonstrated, we demonstrate the clinical application of this technology to successfully identify multiple types of variants using a single test.
  9. J Natl Cancer Inst. 2022 Oct 10. pii: djac160. [Epub ahead of print]
    OPAL Study Group
      BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort.METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types.
    RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types.
    CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.