bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2021‒09‒12
six papers selected by
Sergio Marchini
Humanitas Research
  1. CCNE1 amplification among metastatic sites in patients with gynecologic high-grade serous carcinoma.
  2. TCR Clonality and Genomic Instability Signatures as Prognostic Biomarkers in High Grade Serous Ovarian Cancer.
  3. Multimodal liquid biopsy for early monitoring and outcome prediction of chemotherapy in metastatic breast cancer.
  4. The concurrence of DNA methylation and demethylation is associated with transcription regulation.
  5. Using DNA sequencing data to quantify T cell fraction and therapy response.
  6. DNA double-strand break repair in cancer: A path to achieving precision medicine.
  1. Gynecol Oncol Rep. 2021 Aug;37 100850
    CCNE1 amplification among metastatic sites in patients with gynecologic high-grade serous carcinoma.
    Benjamin Margolis, Fanny Dao, Michael Licciardi, Selim Misirlioglu, Narciso Olvera, Sitharam Ramaswami, Douglas A Levine.
      Objective: We sought to characterize the variability of CCNE1 amplification among metastatic sites of CCNE1 amplified high grade serous carcinoma (HGSC) cases to investigate the feasibility of targeting this alteration for therapeutic purposes.Methods: Patients with CCNE1 amplified HGSC who underwent surgical cytoreduction with metastatic sites were identified from institutional molecular profiling reports and a population of HGSC cases screened using digital droplet PCR (ddPCR). Cases with normal CCNE1 copy number were included as controls. Slides from metastatic sites were cut from formalin-fixed paraffin-embedded tissue blocks, dissected for tumor of > 50% purity, and underwent DNA extraction. CCNE1 copy number was determined by ddPCR. Tumor purity was confirmed with mutant TP53 allele fraction from targeted massively parallel sequencing.
    Results: Four of 15 patients from an institutional database screened by ddPCR were found to have CCNE1 amplification. Three additional patients were identified from a query of institutional commercial clinical reports. Among these 7 CCNE1 amplified cases (2 uterine, 5 ovarian), 5 showed preservation of CCNE1 amplification (copy number > 5) among all metastatic sites. The remaining 2 cases had multiple metastatic sites without preserved CCNE1 amplification. Non-amplified cases had predominantly normal CCNE1 copy number across metastatic sites.
    Conclusions: CCNE1 amplification is an early genomic event in HGSC and is preserved in most metastatic sites suggesting a uniform response to pathway targeting therapies.
    Keywords:  CCNE1; Copy number; Metastasis; Ovarian cancer
    DOI:  https://doi.org/10.1016/j.gore.2021.100850
  2. Cancers (Basel). 2021 Aug 31. pii: 4394. [Epub ahead of print]13(17):
    TCR Clonality and Genomic Instability Signatures as Prognostic Biomarkers in High Grade Serous Ovarian Cancer.
    Julie Lecuelle, Romain Boidot, Hugo Mananet, Valentin Derangère, Juliette Albuisson, Vincent Goussot, Laurent Arnould, Zoé Tharin, Isabelle Ray Coquard, François Ghiringhelli, Caroline Truntzer, Jean-David Fumet.
      PURPOSE: Immune infiltration is a prognostic factor in high-grade serous ovarian carcinoma (HGSC) but immunotherapy efficacy is disappointing. Genomic instability is now used to guide the therapeutic value of PARP inhibitors. We aimed to investigate exome-derived parameters to assess the tumor microenvironment according to genomic instability profile.METHODS: We used the HGSC TCGA (the cancer genome atlas) dataset with genomic characteristics, including homologous recombination deficiency (HRD), copy number variant (CNV) signatures, TCR (T cell receptor) clonality and abundance of tissue-infiltrating immune and stromal cell populations. We then investigated the relationship with survival data.
    RESULTS: In 578 HGSC patients, HRD status, CNV signature 7 and TCR clonality were associated with longer survival. The combination of high CNV signature 7 expression and HRD status or high CNV signature 3 expression and high TCR clonality was associated with a trend towards longer survival compared to each variable alone. Combining T cell infiltrate and TCR clonality improved the prognostic value compared to T cells infiltration alone. Prognostic value of TCR clonality was confirmed in an independent cohort.
    CONCLUSIONS: TCR clonality is an emerging prognostic biomarker that improves T cell infiltrate information. Analysis of TCR clonality combined with genomic instability could be an interesting prognostic biomarker.
    Keywords:  HGSC; HRD; TCR clonality; biomarkers; prognostic
    DOI:  https://doi.org/10.3390/cancers13174394
  3. NPJ Breast Cancer. 2021 Sep 09. 7(1): 115
    Multimodal liquid biopsy for early monitoring and outcome prediction of chemotherapy in metastatic breast cancer.
    Amanda Bortolini Silveira, François-Clément Bidard, Marie-Laure Tanguy, Elodie Girard, Olivier Trédan, Coraline Dubot, William Jacot, Anthony Goncalves, Marc Debled, Christelle Levy, Jean-Marc Ferrero, Christelle Jouannaud, Maria Rios, Marie-Ange Mouret-Reynier, Florence Dalenc, Caroline Hego, Aurore Rampanou, Benoit Albaud, Sylvain Baulande, Frédérique Berger, Jérôme Lemonnier, Shufang Renault, Isabelle Desmoulins, Charlotte Proudhon, Jean-Yves Pierga.
      Circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) are two cancer-derived blood biomarkers that inform on patient prognosis and treatment efficacy in breast cancer. We prospectively evaluated the clinical validity of quantifying both CTCs (CellSearch) and ctDNA (targeted next-generation sequencing). Their combined value as prognostic and early monitoring markers was assessed in 198 HER2-negative metastatic breast cancer patients. All patients were included in the prospective multicenter UCBG study COMET (NCT01745757) and treated by first-line chemotherapy with weekly paclitaxel and bevacizumab. Blood samples were obtained at baseline and before the second cycle of chemotherapy. At baseline, CTCs and ctDNA were respectively detected in 72 and 74% of patients and were moderately correlated (Kendall's τ = 0.3). Only 26 (13%) patients had neither detectable ctDNA nor CTCs. Variants were most frequently observed in TP53 and PIK3CA genes. KMT2C/MLL3 variants detected in ctDNA were significantly associated with a lower CTC count, while the opposite trend was seen with GATA3 alterations. Both CTC and ctDNA levels at baseline and after four weeks of treatment were correlated with survival. For progression-free and overall survival, the best multivariate prognostic model included tumor subtype (triple negative vs other), grade (grade 3 vs other), ctDNA variant allele frequency (VAF) at baseline (per 10% increase), and CTC count at four weeks (≥5CTC/7.5 mL). Overall, this study demonstrates that CTCs and ctDNA have nonoverlapping detection profiles and complementary prognostic values in metastatic breast cancer patients. A comprehensive liquid-biopsy approach may involve simultaneous detection of ctDNA and CTCs.
    DOI:  https://doi.org/10.1038/s41523-021-00319-4
  4. Nat Commun. 2021 Sep 06. 12(1): 5285
    The concurrence of DNA methylation and demethylation is associated with transcription regulation.
    Jiejun Shi, Jianfeng Xu, Yiling Elaine Chen, Jason Sheng Li, Ya Cui, Lanlan Shen, Jingyi Jessica Li, Wei Li.
      The mammalian DNA methylome is formed by two antagonizing processes, methylation by DNA methyltransferases (DNMT) and demethylation by ten-eleven translocation (TET) dioxygenases. Although the dynamics of either methylation or demethylation have been intensively studied in the past decade, the direct effects of their interaction on gene expression remain elusive. Here, we quantify the concurrence of DNA methylation and demethylation by the percentage of unmethylated CpGs within a partially methylated read from bisulfite sequencing. After verifying 'methylation concurrence' by its strong association with the co-localization of DNMT and TET enzymes, we observe that methylation concurrence is strongly correlated with gene expression. Notably, elevated methylation concurrence in tumors is associated with the repression of 40~60% of tumor suppressor genes, which cannot be explained by promoter hypermethylation alone. Furthermore, methylation concurrence can be used to stratify large undermethylated regions with negligible differences in average methylation into two subgroups with distinct chromatin accessibility and gene regulation patterns. Together, methylation concurrence represents a unique methylation metric important for transcription regulation and is distinct from conventional metrics, such as average methylation and methylation variation.
    DOI:  https://doi.org/10.1038/s41467-021-25521-7
  5. Nature. 2021 Sep 08.
    Using DNA sequencing data to quantify T cell fraction and therapy response.
    Robert Bentham, Kevin Litchfield, Thomas B K Watkins, Emilia L Lim, Rachel Rosenthal, Carlos Martínez-Ruiz, Crispin T Hiley, Maise Al Bakir, Roberto Salgado, David A Moore, Mariam Jamal-Hanjani, , Charles Swanton, Nicholas McGranahan.
      The immune microenvironment influences tumour evolution and can be both prognostic and predict response to immunotherapy1,2. However, measurements of tumour infiltrating lymphocytes (TILs) are limited by a shortage of appropriate data. Whole-exome sequencing (WES) of DNA is frequently performed to calculate tumour mutational burden and identify actionable mutations. Here we develop T cell exome TREC tool (T cell ExTRECT), a method for estimation of T cell fraction from WES samples using a signal from T cell receptor excision circle (TREC) loss during V(D)J recombination of the T cell receptor-α gene (TCRA (also known as TRA)). TCRA T cell fraction correlates with orthogonal TIL estimates and is agnostic to sample type. Blood TCRA T cell fraction is higher in females than in males and correlates with both tumour immune infiltrate and presence of bacterial sequencing reads. Tumour TCRA T cell fraction is prognostic in lung adenocarcinoma. Using a meta-analysis of tumours treated with immunotherapy, we show that tumour TCRA T cell fraction predicts immunotherapy response, providing value beyond measuring tumour mutational burden. Applying T cell ExTRECT to a multi-sample pan-cancer cohort reveals a high diversity of the degree of immune infiltration within tumours. Subclonal loss of 12q24.31-32, encompassing SPPL3, is associated with reduced TCRA T cell fraction. T cell ExTRECT provides a cost-effective technique to characterize immune infiltrate alongside somatic changes.
    DOI:  https://doi.org/10.1038/s41586-021-03894-5
  6. Int Rev Cell Mol Biol. 2021 ;pii: S1937-6448(21)00077-0. [Epub ahead of print]364 111-137
    DNA double-strand break repair in cancer: A path to achieving precision medicine.
    Taneisha Gillyard, Jamaine Davis.
      The assessment of DNA damage can be a significant diagnostic for precision medicine. DNA double strand break (DSBs) pathways in cancer are the primary targets in a majority of anticancer therapies, yet the molecular vulnerabilities that underlie each tumor can vary widely making the application of precision medicine challenging. Identifying and understanding these interindividual vulnerabilities enables the design of targeted DSB inhibitors along with evolving precision medicine approaches to selectively kill cancer cells with minimal side effects. A major challenge however, is defining exactly how to target unique differences in DSB repair pathway mechanisms. This review comprises a brief overview of the DSB repair mechanisms in cancer and includes results obtained with revolutionary advances such as CRISPR/Cas9 and machine learning/artificial intelligence, which are rapidly advancing not only our understanding of determinants of DSB repair choice, but also how it can be used to advance precision medicine. Scientific innovation in the methods used to diagnose and treat cancer is converging with advances in basic science and translational research. This revolution will continue to be a critical driver of precision medicine that will enable precise targeting of unique individual mechanisms. This review aims to lay the foundation for achieving this goal.
    Keywords:  Artificial intelligence; DSB repair; Homologous recombination; Machine learning; Nonhomologous end joining; Precision medicine; Risk prediction
    DOI:  https://doi.org/10.1016/bs.ircmb.2021.06.003
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