bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2023‒04‒30
seven papers selected by
Sergio Marchini
Humanitas Research
  1. Regulation of cGAS-STING signalling in cancer: Approach for combination therapy.
  2. Biomarkers for checkpoint inhibitor therapy in mucinous epithelial ovarian cancer.
  3. RAD51 foci as a biomarker predictive of platinum chemotherapy response in ovarian cancer.
  4. A zero-agnostic model for copy number evolution in cancer.
  5. Identification and Characterisation of Infiltrating Immune Cells in Malignant Pleural Mesothelioma Using Spatial Transcriptomics.
  6. The genome-wide mutational consequences of DNA hypomethylation.
  7. Applications of single-cell RNA sequencing in drug discovery and development.
  1. Biochim Biophys Acta Rev Cancer. 2023 Apr 17. pii: S0304-419X(23)00045-8. [Epub ahead of print]1878(3): 188896
    Regulation of cGAS-STING signalling in cancer: Approach for combination therapy.
    Hitesh Vasiyani, Bhumika Wadhwa, Rajesh Singh.
      Innate immunity plays an important role not only during infection but also homeostatic role during stress conditions. Activation of the immune system including innate immune response plays a critical role in the initiation and progression of tumorigenesis. The innate immune sensor recognizes pathogen-associated molecular patterns (PAMPs) and activates cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) (cGAS-STING) and induces type-1 immune response during viral and bacterial infection. cGAS-STING is regulated differently in conditions like cellular senescence and DNA damage in normal and tumor cells and is implicated in the progression of tumors from different origins. cGAS binds to cytoplasmic dsDNA and synthesize cyclic GMP-AMP (2'3'-cGAMP), which selectively activates STING and downstream IFN and NF-κB activation. We here reviewed the cGAS-STING signalling pathway and its cross-talk with other pathways to modulate tumorigenesis. Further, the review also focused on emerging studies that targeted the cGAS-STING pathway for developing targeted therapeutics and combinatorial regimens for cancer of different origins.
    Keywords:  Cancer; Chromosomal instability; Classical therapy; Combinatorial therapy; Immunomodulatory; Tumor microenvironment; cGAS-STING
    DOI:  https://doi.org/10.1016/j.bbcan.2023.188896
  2. Int J Gynecol Cancer. 2023 Apr 24. pii: ijgc-2023-004360. [Epub ahead of print]
    Biomarkers for checkpoint inhibitor therapy in mucinous epithelial ovarian cancer.
    Thomas Bartl, Anita Alberts, Sofia-Christina Papadopoulos, Andrea Wolf, Leonhard Muellauer, Gerda Hofstetter, Christoph Grimm, Dan Cacsire Castillo-Tong.
      OBJECTIVE: The prognosis of patients with advanced stage mucinous epithelial ovarian cancer remains poor due to a modest response to platinum-based chemotherapy and the absence of therapeutic alternatives. As targeted approaches may help to overcome these limitations, the present study evaluates biomarkers indicative of potential immune-checkpoint inhibitor therapy response.METHODS: All patients who underwent primary cytoreductive surgery from January 2001 to December 2020 and for whom formalin-fixed paraffin-embedded tissue samples were available were included (n=35; 12 International Federation of Gynecology and Obstetrics (FIGO) stage ≥IIb). To define sub-groups potentially suitable for checkpoint inhibition, expression of programmed death-ligand 1 (PD-L1), tumor-infiltrating lymphocytes (CD3+, CD8+, CD20+, CD45+, CD68+, FoxP3+), and AT-rich interactive domain-containing protein 1A (ARID1A) immunostaining were evaluated in whole tissue sections and compared with clinicopathologic parameters and next-generation sequencing results, where available (n=11). Survival analyses were performed to assess whether identified sub-groups were associated with specific clinical outcomes.
    RESULTS: In total, 34.3% (n=12/35) of tumors were PD-L1 positive. PD-L1 expression was associated with infiltrative histotype (p=0.027) and correlated with higher CD8+ (r=0.577, p<0.001) and CD45+ (r=0.424, p=0.011), but reduced ARID1A expression (r=-4.39, p=0.008). CD8+ expression was associated with longer progression-free survival (hazard ratio (HR) 0.85 (95% CI 0.72 to 0.99), p=0.047) and disease-specific survival (HR 0.85 (95% CI 0.73 to 1.00), p=0.044) in the sub-group with FIGO stage ≥IIb. Three (8.6%) samples demonstrated high PD-L1 expression at a combined positive score of >10, which was associated with increased CD8+ expression (p=0.010) and loss of ARID1A expression (p=0.034). Next-generation sequencing, which was available for all samples with a combined positive score of >10, showed KRAS mutations, BRCA wild-type status, and mismatch repair proficiency in all cases, but did not reveal genetic alterations potentially associated with a pro-immunogenic tumor environment.
    CONCLUSIONS: A sub-group of mucinous ovarian cancers appear to demonstrate a pro-immunogenic tumor environment with high PD-L1 expression, decreased ARID1A expression, and characteristic tumor-infiltrating lymphocyte infiltration patterns. Further clinical validation of anti-PD-L1/PD-1 targeting in selected mucinous ovarian cancers appears promising.
    Keywords:  cystadenocarcinoma, mucinous
    DOI:  https://doi.org/10.1136/ijgc-2023-004360
  3. Clin Cancer Res. 2023 Apr 25. pii: CCR-22-3335. [Epub ahead of print]
    RAD51 foci as a biomarker predictive of platinum chemotherapy response in ovarian cancer.
    Amanda J Compadre, Lillian N van Biljon, Mark C Valentine, Alba Llop-Guevara, Emily Graham, Bisiayo Fashemi, Andrea Herencia-Ropero, Emilee N Kotnik, Isaac Cooper, Shariska P Harrington, Lindsay M Kuroki, Carolyn K McCourt, Andrea R Hagemann, Premal H Thaker, David G Mutch, Matthew A Powell, Lulu Sun, Nima Mosammaparast, Violeta Serra, Peinan Zhao, Elena Lomonosova, Dineo Khabele, Mary M Mullen.
      PURPOSE: To determine the ability of RAD51 foci to predict platinum chemotherapy response in high-grade serous ovarian cancer (HGSOC) patient-derived samples.EXPERIMENTAL DESIGN: RAD51 and γH2AX nuclear foci were evaluated by immunofluorescence in HGSOC patient-derived cell lines (n=5), organoids (n=11), and formalin-fixed, paraffin-embedded tumor samples (discovery n=31, validation n=148). Samples were defined as RAD51-High if >10% of geminin-positive cells had ≥5 RAD51 foci. Associations between RAD51 scores, platinum chemotherapy response, and survival were evaluated.
    RESULTS: RAD51 scores correlated with in vitro response to platinum chemotherapy in established and primary ovarian cancer cell lines (Pearson r=0.96, P=0.01). Organoids from platinum-nonresponsive tumors had significantly higher RAD51 scores than those from platinum-responsive tumors (P<0.001). In a discovery cohort, RAD51-Low tumors were more likely to have a pathologic complete response (RR 5.28, P<0.001) and to be platinum-sensitive (RR ∞, P = 0.05). The RAD51 score was predictive of chemotherapy response score (AUC 0.90, 95% CI 0.78-1.0; P<0.001). A novel automatic quantification system accurately reflected the manual assay (92%). In a validation cohort, RAD51-Low tumors were more likely to be platinum-sensitive (RR ∞, P < 0.001) than RAD51-High tumors. Moreover, RAD51-Low status predicted platinum sensitivity with 100% positive predictive value and was associated with better progression-free (HR 0.53, 95% CI 0.33-0.85, P<0.001) and overall survival (HR 0.43, 95% CI 0.25-0.75, P=0.003) than RAD51-High status.
    CONCLUSIONS: RAD51 foci are a robust marker of platinum chemotherapy response and survival in ovarian cancer. The utility of RAD51 foci as a predictive biomarker for HGSOC should be tested in clinical trials.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-22-3335
  4. bioRxiv. 2023 Apr 12. pii: 2023.04.10.536302. [Epub ahead of print]
    A zero-agnostic model for copy number evolution in cancer.
    Henri Schmidt, Palash Sashittal, Benjamin J Raphael.
      Motivation: New low-coverage single-cell DNA sequencing technologies enable the measurement of copy number profiles from thousands of individual cells within tumors. From this data, one can infer the evolutionary history of the tumor by modeling transformations of the genome via copy number aberrations. A widely used model to infer such copy number phylogenies is the copy number transformation (CNT) model in which a genome is represented by an integer vector and a copy number aberration is an event that either increases or decreases the number of copies of a contiguous segment of the genome. The CNT distance between a pair of copy number profiles is the minimum number of events required to transform one profile to another. While this distance can be computed efficiently, no efficient algorithm has been developed to find the most parsimonious phylogeny under the CNT model.Results: We introduce the zero-agnostic copy number transformation (ZCNT) model, a simplification of the CNT model that allows the amplification or deletion of regions with zero copies. We derive a closed form expression for the ZCNT distance between two copy number profiles and show that, unlike the CNT distance, the ZCNT distance forms a metric. We leverage the closed-form expression for the ZCNT distance and an alternative characterization of copy number profiles to derive polynomial time algorithms for two natural relaxations of the small parsimony problem on copy number profiles. While the alteration of zero copy number regions allowed under the ZCNT model is not biologically realistic, we show on both simulated and real datasets that the ZCNT distance is a close approximation to the CNT distance. Extending our polynomial time algorithm for the ZCNT small parsimony problem, we develop an algorithm, Lazac , for solving the large parsimony problem on copy number profiles. We demonstrate that Lazac outperforms existing methods for inferring copy number phylogenies on both simulated and real data.
    Availability: Lazac is implemented in C++17 and is freely available at: github.com/raphaelgroup/lazac-copy-number .
    DOI:  https://doi.org/10.1101/2023.04.10.536302
  5. Methods Protoc. 2023 Mar 28. pii: 35. [Epub ahead of print]6(2):
    Identification and Characterisation of Infiltrating Immune Cells in Malignant Pleural Mesothelioma Using Spatial Transcriptomics.
    Dmitrii Shek, Brian Gloss, Joey Lai, Li Ma, Hui E Zhang, Matteo S Carlino, Hema Mahajan, Adnan Nagrial, Bo Gao, Scott A Read, Golo Ahlenstiel.
      Increasing evidence strongly supports the key role of the tumour microenvironment in response to systemic therapy, particularly immune checkpoint inhibitors (ICIs). The tumour microenvironment is a complex tapestry of immune cells, some of which can suppress T-cell immunity to negatively impact ICI therapy. The immune component of the tumour microenvironment, although poorly understood, has the potential to reveal novel insights that can impact the efficacy and safety of ICI therapy. Successful identification and validation of these factors using cutting-edge spatial and single-cell technologies may enable the development of broad acting adjunct therapies as well as personalised cancer immunotherapies in the near future. In this paper we describe a protocol built upon Visium (10x Genomics) spatial transcriptomics to map and characterise the tumour-infiltrating immune microenvironment in malignant pleural mesothelioma. Using ImSig tumour-specific immune cell gene signatures and BayesSpace Bayesian statistical methodology, we were able to significantly improve immune cell identification and spatial resolution, respectively, improving our ability to analyse immune cell interactions within the tumour microenvironment.
    Keywords:  immune checkpoint inhibitors; mesothelioma; research protocol; spatial analysis
    DOI:  https://doi.org/10.3390/mps6020035
  6. Sci Rep. 2023 Apr 27. 13(1): 6874
    The genome-wide mutational consequences of DNA hypomethylation.
    Nicolle Besselink, Janneke Keijer, Carlo Vermeulen, Sander Boymans, Jeroen de Ridder, Arne van Hoeck, Edwin Cuppen, Ewart Kuijk.
      DNA methylation is important for establishing and maintaining cell identity and for genomic stability. This is achieved by regulating the accessibility of regulatory and transcriptional elements and the compaction of subtelomeric, centromeric, and other inactive genomic regions. Carcinogenesis is accompanied by a global loss in DNA methylation, which facilitates the transformation of cells. Cancer hypomethylation may also cause genomic instability, for example through interference with the protective function of telomeres and centromeres. However, understanding the role(s) of hypomethylation in tumor evolution is incomplete because the precise mutational consequences of global hypomethylation have thus far not been systematically assessed. Here we made genome-wide inventories of all possible genetic variation that accumulates in single cells upon the long-term global hypomethylation by CRISPR interference-mediated conditional knockdown of DNMT1. Depletion of DNMT1 resulted in a genomewide reduction in DNA methylation. The degree of DNA methylation loss was similar to that observed in many cancer types. Hypomethylated cells showed reduced proliferation rates, increased transcription of genes, reactivation of the inactive X-chromosome and abnormal nuclear morphologies. Prolonged hypomethylation was accompanied by increased chromosomal instability. However, there was no increase in mutational burden, enrichment for certain mutational signatures or accumulation of structural variation to the genome. In conclusion, the primary consequence of hypomethylation is genomic instability, which in cancer leads to increased tumor heterogeneity and thereby fuels cancer evolution.
    DOI:  https://doi.org/10.1038/s41598-023-33932-3
  7. Nat Rev Drug Discov. 2023 Apr 28.
    Applications of single-cell RNA sequencing in drug discovery and development.
    Bram Van de Sande, Joon Sang Lee, Euphemia Mutasa-Gottgens, Bart Naughton, Wendi Bacon, Jonathan Manning, Yong Wang, Jack Pollard, Melissa Mendez, Jon Hill, Namit Kumar, Xiaohong Cao, Xiao Chen, Mugdha Khaladkar, Ji Wen, Andrew Leach, Edgardo Ferran.
      Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.
    DOI:  https://doi.org/10.1038/s41573-023-00688-4
This page is being maintained by Thomas Krichel. It was last updated on 2023‒05‒08 at 07:28:17.