bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2023–03–05
seven papers selected by
Sergio Marchini, Humanitas Research
  1. iSC.MEB: an R package for multi-sample spatial clustering analysis of spatial transcriptomics data.
  2. [Homologous recombination deficiency in epithelial ovarian cancers: from molecular characterization to patient journey].
  3. A RAD51 functional assay as a candidate test for homologous recombination deficiency in ovarian cancer.
  4. Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer.
  5. STEEL enables high-resolution delineation of spatiotemporal transcriptomic data.
  6. Dynamic changes in circulating tumor DNA assessed by shallow whole-genome sequencing associate with clinical efficacy of checkpoint inhibitors in NSCLC.
  7. Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST.
  1. Bioinform Adv. 2023 ;3(1): vbad019
    iSC.MEB: an R package for multi-sample spatial clustering analysis of spatial transcriptomics data.
    Xiao Zhang, Wei Liu, Fangda Song, Jin Liu.
       Summary: Emerging spatially resolved transcriptomics (SRT) technologies are powerful in measuring gene expression profiles while retaining tissue spatial localization information and typically provide data from multiple tissue sections. We have previously developed the tool SC.MEB-an empirical Bayes approach for SRT data analysis using a hidden Markov random field. Here, we introduce an extension to SC.MEB, denoted as integrated spatial clustering with hidden Markov random field using empirical Bayes (iSC.MEB) that permits the users to simultaneously estimate the batch effect and perform spatial clustering for low-dimensional representations of multiple SRT datasets. We demonstrate that iSC.MEB can provide accurate cell/domain detection results using two SRT datasets.
    Availability and implementation: iSC.MEB is implemented in an open-source R package, and source code is freely available at https://github.com/XiaoZhangryy/iSC.MEB. Documentation and vignettes are provided on our package website (https://xiaozhangryy.github.io/iSC.MEB/index.html).
    Supplementary information: Supplementary data are available at Bioinformatics Advances online.
    DOI:  https://doi.org/10.1093/bioadv/vbad019
  2. Bull Cancer. 2023 Feb 28. pii: S0007-4551(23)00077-2. [Epub ahead of print]
    [Homologous recombination deficiency in epithelial ovarian cancers: from molecular characterization to patient journey].
    Stanislas Quesada, Jérôme Solassol, Isabelle Ray-Coquard, Michel Fabbro.
      High-grade serous ovarian carcinoma (HGSOC), the most frequent and aggressive form of epithelial ovarian cancer is characterized in half of cases by homologous recombination deficiency (HRD). This molecular alteration is defined by distinct causes and consequences. The main and most characterized cause is the presence of an alteration affecting BRCA1 and BRCA2 genes. Regarding consequences, a specific genomic instability leads to increased sensitivity to platinum salts and poly (ADP-ribose) polymerase (PARPi) inhibitors. This latter point enabled the advent of PARPi in first and second line maintenance. As such, the initial and rapid evaluation of HRD status with molecular tests is a key step in the management of HGSOC. Until recently, the range of tests offered proved to be very limited and suffered from technical and medical limitations. This has recently led to the development and validation of alternatives, including academic ones. This "state of the art" review will bring a synthesis concerning the assessment of HRD status in HGSOCs. After a brief introduction of HRD (including main causes and consequences) and of its predictive value regarding PARPi, we will discuss the limitations of current molecular tests and the existing alternatives. Finally, we will contextualize this to the situation in France, with special consideration concerning the positioning and the financial coverage of these tests, with the perspective of optimizing patient management .
    Keywords:  BRCA1/2; Carcinome séreux ovarien de haut grade; Déficit de la recombinaison homologue; High-grade serous ovarian cancer; Homologous recombination deficiency; PARPi; Theranostic; Théranostique
    DOI:  https://doi.org/10.1016/j.bulcan.2023.02.004
  3. Gynecol Oncol. 2023 Mar 01. pii: S0090-8258(23)00026-4. [Epub ahead of print]171 106-113
    A RAD51 functional assay as a candidate test for homologous recombination deficiency in ovarian cancer.
    Félix Blanc-Durand, Elisa Yaniz-Galende, Alba Llop-Guevara, Catherine Genestie, Violeta Serra, Andrea Herencia-Ropero, Christophe Klein, Dominique Berton, Alain Lortholary, Nadine Dohollou, Christophe Desauw, Michel Fabbro, Emmanuelle Malaurie, Nathalie Bonichon-Lamaichhane, Coraline Dubot, Jean Emmanuel Kurtz, Gaëtan de Rauglaudre, Nadia Raban, Annick Chevalier-Place, Gwenael Ferron, Marie-Christine Kaminsky, Claire Kramer, Etienne Rouleau, Alexandra Leary.
       RATIONALE: Homologous recombination deficiency (HRD), defined as BRCA1/2 mutation (BRCAmut) or high genomic instability, is used to identify ovarian cancer (OC) patients most likely to benefit from PARP inhibitors. While these tests are useful, they are imperfect. Another approach is to measure the capacity of tumor cells to form RAD51 foci in the presence of DNA damage using an immunofluorescence assay (IF). We aimed to describe for the first time this assay in OC and correlate it to platinum response and BRCAmut.
    METHODS: Tumor samples were prospectively collected from the randomized CHIVA trial of neoadjuvant platinum +/- nintedanib. IF for RAD51, GMN and gH2AX was performed on FFPE blocks. Tumors were considered RAD51-low if ≤10% of GMN-positive tumor cells had ≥5 RAD51 foci. BRCAmut were identified by NGS.
    RESULTS: 155 samples were available. RAD51 assay was contributive for 92% of samples and NGS available for 77%. gH2AX foci confirmed the presence of significant basal DNA damage. 54% of samples were considered HRD by RAD51 and presented higher overall response rates to neoadjuvant platinum (P = 0.04) and longer progression-free survival (P = 0.02). In addition, 67% of BRCAmut were HRD by RAD51. Among BRCAmut, RAD51-high tumors seem to harbor poorer response to chemotherapy (P = 0.02).
    CONCLUSIONS: We evaluated a functional assay of HR competency. OC demonstrate high levels of DNA damage, yet 54% fail to form RAD51 foci. These RAD51-low OC tend to be more sensitive to neoadjuvant platinum. The RAD51 assay also identified a subset of RAD51-high BRCAmut tumors with unexpected poor platinum response.
    Keywords:  BRCA; Homologous recombination; Neoadjuvant chemotherapy; Ovarian cancer; RAD51
    DOI:  https://doi.org/10.1016/j.ygyno.2023.01.026
  4. Nat Genet. 2023 Feb 27.
    Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer.
    Nikki L Burdett, Madelynne O Willis, Kathryn Alsop, Allison L Hunt, Ahwan Pandey, Phineas T Hamilton, Tamara Abulez, Xuan Liu, Therese Hoang, Stuart Craig, Sian Fereday, Joy Hendley, Dale W Garsed, Katy Milne, Shreena Kalaria, Ashley Marshall, Brian L Hood, Katlin N Wilson, Kelly A Conrads, Kathleen I Pishas, Sumitra Ananda, Clare L Scott, Yoland Antill, Orla McNally, Linda Mileshkin, Anne Hamilton, George Au-Yeung, Lisa Devereux, Heather Thorne, Andrea Bild, Nicholas W Bateman, G Larry Maxwell, Jeffrey T Chang, Thomas P Conrads, Brad H Nelson, David D L Bowtell, Elizabeth L Christie.
      High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients.
    DOI:  https://doi.org/10.1038/s41588-023-01320-2
  5. Brief Bioinform. 2023 Mar 01. pii: bbad068. [Epub ahead of print]
    STEEL enables high-resolution delineation of spatiotemporal transcriptomic data.
    Yamao Chen, Shengyu Zhou, Ming Li, Fangqing Zhao, Ji Qi.
      Advances in spatial transcriptomics enlarge the use of single cell technologies to unveil the expression landscape of the tissues with valuable spatial context. Here, we propose an unsupervised and manifold learning-based algorithm, Spatial Transcriptome based cEll typE cLustering (STEEL), which identifies domains from spatial transcriptome by clustering beads exhibiting both highly similar gene expression profiles and close spatial distance in the manner of graphs. Comprehensive evaluation of STEEL on spatial transcriptomic datasets from 10X Visium platform demonstrates that it not only achieves a high resolution to characterize fine structures of mouse brain but also enables the integration of multiple tissue slides individually analyzed into a larger one. STEEL outperforms previous methods to effectively distinguish different cell types/domains of various tissues on Slide-seq datasets, featuring in higher bead density but lower transcript detection efficiency. Application of STEEL on spatial transcriptomes of early-stage mouse embryos (E9.5-E12.5) successfully delineates a progressive development landscape of tissues from ectoderm, mesoderm and endoderm layers, and further profiles dynamic changes on cell differentiation in heart and other organs. With the advancement of spatial transcriptome technologies, our method will have great applicability on domain identification and gene expression atlas reconstruction.
    DOI:  https://doi.org/10.1093/bib/bbad068
  6. Mol Oncol. 2023 Feb 28.
    Dynamic changes in circulating tumor DNA assessed by shallow whole-genome sequencing associate with clinical efficacy of checkpoint inhibitors in NSCLC.
    Caterina Carbonell, Joan Frigola, Nuria Pardo, Ana Callejo, Patricia Iranzo, Augusto Valdivia, Ilaria Priano, Susana Cedrés, Alex Martinez-Marti, Alejandro Navarro, Laura Lenza, Mireia Soleda, Javier Gonzalo-Ruiz, Ana Vivancos, Miriam Sansó, Enric Carcereny, Teresa Morán, Ramon Amat, Enriqueta Felip.
      Immune checkpoint inhibitors (ICIs) targeting the PD-1/PD-L1 axis are the main therapeutic option for patients with advanced non-small cell lung cancer (NSCLC) without a druggable oncogenic alteration. Nevertheless, only a portion of patients benefit from this type of treatment. Here, we assessed the value of shallow whole-genome sequencing (sWGS) on plasma samples to monitor ICIs benefit. We applied sWGS on cell-free DNA (cfDNA) extracted from plasma samples of 45 patients with metastatic NSCLC treated with ICIs. Over 150 samples were obtained before ICIs treatment initiation and at several time points throughout treatment. From sWGS data, we computed the tumor fraction (TFx) and somatic copy number alterations (SCNAs) burden and associated them with ICIs benefit and clinical features. TFx at baseline correlated with metastatic lesions at the bone and the liver, and high TFx (≥10%) associated with ICIs benefit. Moreover, its assessment in on-treatment samples was able to better predict clinical efficacy, regardless of the TFx levels at baseline. Finally, for a subset of patients for whom SCNAs burden could be computed, increased burden correlated with diminished benefit following ICIs treatment. Thus, our data indicate that the analysis of cfDNA by sWGS enables the monitoring of two potential biomarkers-TFx and SCNAs burden-of ICIs benefit in a cost-effective manner, facilitating multiple serial-sample analyses. Larger cohorts will be needed to establish its clinical potential.
    Keywords:  Liquid biopsy; NSCLC; SCNAs burden; aneuploidy; biomarker; cfDNA; copy number alterations; ctDNA; immune checkpoint inhibitors; low-depth whole-genome sequencing; shallow whole-genome sequencing; tumor fraction
    DOI:  https://doi.org/10.1002/1878-0261.13409
  7. Nat Commun. 2023 Mar 01. 14(1): 1155
    Spatially informed clustering, integration, and deconvolution of spatial transcriptomics with GraphST.
    Yahui Long, Kok Siong Ang, Mengwei Li, Kian Long Kelvin Chong, Raman Sethi, Chengwei Zhong, Hang Xu, Zhiwei Ong, Karishma Sachaphibulkij, Ao Chen, Li Zeng, Huazhu Fu, Min Wu, Lina Hsiu Kim Lim, Longqi Liu, Jinmiao Chen.
      Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools for three key tasks, spatial clustering, multisample integration, and cell-type deconvolution. We present GraphST, a graph self-supervised contrastive learning method that fully exploits spatial transcriptomics data to outperform existing methods. It combines graph neural networks with self-supervised contrastive learning to learn informative and discriminative spot representations by minimizing the embedding distance between spatially adjacent spots and vice versa. We demonstrated GraphST on multiple tissue types and technology platforms. GraphST achieved 10% higher clustering accuracy and better delineated fine-grained tissue structures in brain and embryo tissues. GraphST is also the only method that can jointly analyze multiple tissue slices in vertical or horizontal integration while correcting batch effects. Lastly, GraphST demonstrated superior cell-type deconvolution to capture spatial niches like lymph node germinal centers and exhausted tumor infiltrating T cells in breast tumor tissue.
    DOI:  https://doi.org/10.1038/s41467-023-36796-3
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