bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2022‒09‒11
four papers selected by
Sergio Marchini
Humanitas Research

  1. Cancers (Basel). 2022 Aug 27. pii: 4157. [Epub ahead of print]14(17):
      Homologous recombination deficiency (HRD) is a prevalent in approximately 17% of tumors and is associated with enhanced sensitivity to anticancer therapies inducing double-strand DNA breaks. Accurate detection of HRD would therefore allow improved patient selection and outcome of conventional and targeted anticancer therapies. However, current clinical assessment of HRD mainly relies on determining germline BRCA1/2 mutational status and is insufficient for adequate patient stratification as mechanisms of HRD occurrence extend beyond functional BRCA1/2 loss. HRD, regardless of BRCA1/2 status, is associated with specific forms of genomic and mutational signatures termed HRD scar. Detection of this HRD scar might therefore be a more reliable biomarker for HRD. This review discusses and compares different methods of assessing HRD and HRD scar, their advances into the clinic, and their potential implications for precision oncology.
    Keywords:  DNA repair; biomarkers; cancer; homologous recombination; homologous recombination deficiency; homologous recombination deficiency scar; precision oncology
  2. Bioinformatics. 2022 Sep 05. pii: btac605. [Epub ahead of print]
      MOTIVATION: Unveiling the heterogeneity in the tissues is crucial to explore cell-cell interactions and cellular targets of human diseases. Spatial transcriptomics (ST) supplies spatial gene expression profile which has revolutionized our biological understanding, but variations in cell type proportions of each spot with dozens of cells would confound downstream analysis. Therefore, deconvolution of ST has been an indispensable step and a technical challenge towards the higher-resolution panorama of tissues.RESULTS: Here, we propose a novel ST deconvolution method called SD2 integrating spatial information of ST data and embracing an important characteristic, dropout, which is traditionally considered as an obstruction in single-cell RNA sequencing data (scRNA-seq) analysis. First, we extract the dropout-based genes as informative features from ST and scRNA-seq data by fitting a Michaelis-Menten function. After synthesizing pseudo-ST spots by randomly composing cells from scRNA-seq data, auto-encoder is applied to discover low-dimensional and non-linear representation of the real- and pseudo-ST spots. Next, we create a graph containing embedded profiles as nodes, and edges determined by transcriptional similarity and spatial relationship. Given the graph, a graph convolutional neural network is used to predict the cell-type compositions for real-ST spots. We benchmark the performance of SD2 on the simulated seqFISH+ dataset with different resolutions and measurements which show superior performance compared with the state-of-the-art methods. SD2 is further validated on three real-world datasets with different ST technologies, and demonstrates the capability to localize cell-type composition accurately with quantitive evidence. Finally, ablation study is conducted to verify the contribution of different modules proposed in SD2.
    AVAILABILITY: The SD2 is freely available in github ( and Zenodo (
  3. Eur J Cancer. 2022 Sep 03. pii: S0959-8049(22)00447-6. [Epub ahead of print]174 221-231
    PAOLA1/ENGOT-ov25 investigators
      BACKGROUND: PAOLA-1/ENGOT-ov25 (NCT02477644) demonstrated a significant progression-free survival (PFS) benefit with maintenance olaparib plus bevacizumab versus placebo plus bevacizumab in newly diagnosed, advanced ovarian cancer. We report the prespecified main second progression-free survival (PFS2) analysis for PAOLA-1.METHODS: This randomised, double-blind, phase III trial was conducted in 11 countries. Eligible patients had newly diagnosed, advanced, high-grade ovarian cancer and were in response after first-line platinum-based chemotherapy plus bevacizumab. Patients were randomised 2:1 to olaparib (300 mg twice daily) or placebo for up to 24 months; all patients received bevacizumab (15 mg/kg every 3 weeks) for up to 15 months. Primary PFS end-point was reported previously. Time from randomisation to second disease progression or death was a key secondary end-point included in the hierarchical-testing procedure.
    RESULTS: After a median follow-up of 35.5 months and 36.5 months, respectively, median PFS2 was 36.5 months (olaparib plus bevacizumab) and 32.6 months (placebo plus bevacizumab), hazard ratio 0.78; 95% confidence interval (CI) 0.64-0.95; P = 0.0125. Median time to second subsequent therapy or death was 38.2 months (olaparib plus bevacizumab) and 31.5 months (placebo plus bevacizumab), hazard ratio 0.78; 95% CI 0.64-0.95; P = 0.0115. Seventy-two (27%) patients in the placebo plus bevacizumab group received a poly(ADP-ribose) polymerase inhibitor as first subsequent therapy. No new safety signals were observed for olaparib plus bevacizumab.
    CONCLUSION: In newly diagnosed, advanced ovarian cancer, maintenance olaparib plus bevacizumab provided continued benefit beyond first progression, with a significant PFS2 improvement and a time to second subsequent therapy or death delay versus placebo plus bevacizumab.
    Keywords:  Antiangiogenic agent; Bevacizumab; Olaparib; Ovarian cancer; PARP inhibitor; Second progression-free survival
  4. J Exp Clin Cancer Res. 2022 Sep 07. 41(1): 268
      As our understanding of the mechanisms of cancer treatment has increased, a growing number of studies demonstrate pathways through which DNA damage repair (DDR) affects the immune system. At the same time, the varied response of patients to immune checkpoint blockade (ICB) therapy has prompted the discovery of various predictive biomarkers and the study of combination therapy. Here, our investigation explores the interactions involved in combination therapy, accompanied by a review that summarizes currently identified and promising predictors of response to immune checkpoint inhibitors (ICIs) that are useful for classifying oncology patients. In addition, this work, which discusses immunogenicity and several components of the tumor immune microenvironment, serves to illustrate the mechanism by which higher response rates and improved efficacy of DDR inhibitors (DDRi) in combination with ICIs are achieved.
    Keywords:  ATM/ATR/Chk1; DNA damage repair; DNA damage repair inhibitors; Immune checkpoint blockade; Immune checkpoint inhibitor; cGAS/STING