bims-tumhet 2022-09-25 papers

Issue of 2022–09–25
eight papers selected by
Sergio Marchini, Humanitas Research

Adv Biol (Weinh). 2022 Sep 18. e2200060

Unraveling the Transcriptomic Signatures of Homologous Recombination Deficiency in Ovarian Cancers.

Jae Jun Lee, Hyun Ju Kang, Stephanie S Kim, Clémentine Charton, Jinho Kim, Jin-Ku Lee.

Homologous recombination deficiency (HRD) is a crucial driver of tumorigenesis by inducing impaired repair of double-stranded DNA breaks. Although HRD possibly triggers the production of numerous tumor neoantigens that sufficiently stimulate and activate various tumor-immune responses, a comprehensive understanding of the HRD-associated tumor microenvironment is elusive. To investigate the effect of HRD on the selective enrichment of transcriptomic signatures, 294 cases from The Cancer Genome Atlas-Ovarian Cancer project with both RNA-sequencing and SNP array data are analyzed. Differentially expressed gene analysis and network analysis are performed to identify HRD-specific signatures. Gene-sets associated with mitochondrial activation, including enhanced oxidative phosphorylation (OxPhos), are significantly enriched in the HRD-high group. Furthermore, a wide range of immune cell activation signatures is enriched in HRD-high cases of high-grade serous ovarian cancer (HGSOC). On further cell-type-specific analysis, M1-like macrophage genes are significantly enriched in HRD-high HGSOC cases, whereas M2-macrophage-related genes are not. The immune-response-associated genomic features, including tumor mutation rate, neoantigens, and tumor mutation burdens, correlated with HRD scores. In conclusion, the results of this study highlight the biological properties of HRD, including enhanced energy metabolism, increased tumor neoantigens and tumor mutation burdens, and consequent exacerbation of immune responses, particularly the enrichment of M1-like macrophages in HGSOC cases.

Keywords: M1-like macrophages; homologous recombination deficiency; immune responses; ovarian cancer; tumor mutation rate

DOI: https://doi.org/10.1002/adbi.202200060

Fundam Clin Pharmacol. 2022 Sep 21.

Therapeutic targeting of DNA damage repair pathways guided by homologous recombination deficiency scoring in ovarian cancers.

Chunxiu Lin, Peng Liu, Chaowen Shi, Lipeng Qiu, Dongsheng Shang, Ziwen Lu, Zhigang Tu, Hanqing Liu.

The susceptibility of cells to DNA damage and their DNA repair ability are crucial for cancer therapy. Homologous recombination is one of the major repairing mechanisms for DNA double-strand breaks. Approximately half of ovarian cancer (OvCa) cells harbor homologous recombination deficiency (HRD). Considering that HRD is a major hallmark of OvCas, scholars proposed HRD scoring to evaluate the HRD degree and guide the choice of therapeutic strategies for OvCas. In the last decade, synthetic lethal strategy by targeting poly (ADP-ribose) polymerase (PARP) in HR-deficient OvCas has attracted considerable attention in view of its favorable clinical effort. We therefore suggested that the uses of other DNA damage/repair-targeted drugs in HR-deficient OvCas might also offer better clinical outcome. Here, we reviewed the current small molecule compounds which targeted DNA damage/repair pathways, and discussed the HRD scoring system to guide their clinical uses.

Keywords: DNA repair; PAPR inhibitors; epigenetic modifications; ovarian cancer; small molecular drugs

DOI: https://doi.org/10.1111/fcp.12834

Pathologica. 2022 Aug;114(4): 288-294

In-house testing for homologous recombination repair deficiency (HRD) testing in ovarian carcinoma: a feasibility study comparing AmoyDx HRD Focus panel with Myriad myChoiceCDx assay.

Caterina Fumagalli, Ilaria Betella, Alberto Ranghiero, Elena Guerini-Rocco, Giulio Bonaldo, Alessandra Rappa, Davide Vacirca, Nicoletta Colombo, Massimo Barberis.

Background: Homologous recombination repair (HRR) is the main mechanism of repair of DNA double-strand breaks. Its deficiency (HRD) is a common feature of epithelial ovarian cancers (EOCs). BRCA1/2 mutations and/or other aberrations in genes of HRR are well known causes of HRD and genomic instability. Poly ADP-ribose polymerase inhibitors (PARPi) have revolutionized the management of BRCA mutant EOCs and demonstrated activity in HRD tumor cells. Determining HRD status can provide informations on the magnitude of benefit for PARPi therapy. Myriad MyChoice CDx is a next generation sequencing- based in vitro diagnostic test that assesses the Genomic Instability Score (GIS) which is an algorithmic measurement of loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions using DNA isolated from formalin-fixed paraffin embedded tumor tissue specimens. However Myriad MyChoice CDx, is a centrally performed and costly assay, with no reimbursement scheduled, at least in Italy.
Methods: In this report, we described our experience in performing the HRD Focus AmoyDx (Amoy Diagnostics Ltd, Xiamen, Fujian, China) on the same samples of EOCs evaluated with Myriad MyChoiceCDx assay.
Results: The overall percent agreement between AmoyDx and Myriad was 87.8% (65 of 74 tumors tested). All the 36 AmoyDx negative cases were confirmed to be negative by Myriad (negative predictive value, 100%).
Conclusions: The concordance of the results with the gold standard Myriad MyChoice CDx assay suggest the feasibility and reliability of HRD testing in diagnostic laboratories with high-throughput NGS platforms and qualified personnel.

Keywords: HRD; genomic scar; homologous recombination deficiency; ovarian cancer

DOI: https://doi.org/10.32074/1591-951X-791

Int J Mol Sci. 2022 Sep 17. pii: 10892. [Epub ahead of print]23(18):

Sequential Targeting of PLK1 and PARP1 Reverses the Resistance to PARP Inhibitors and Enhances Platin-Based Chemotherapy in BRCA-Deficient High-Grade Serous Ovarian Cancer with KRAS Amplification.

Khayal Gasimli, Monika Raab, Morva Tahmasbi Rad, Elisabeth Kurunci-Csacsko, Sven Becker, Klaus Strebhardt, Mourad Sanhaji.

Ovarian cancer (OC) accounts for approximately 4% of cancer deaths in women worldwide and is the deadliest gynecologic malignancy. High-grade serous ovarian cancer (HGSOC) is the most predominant ovarian cancer, in which BRCA1/2 gene mutation ranges from 3 to 27%. PARP inhibitors (PARPi) have shown promising results as a synthetically lethal therapeutic approach for BRCA mutant and recurrent OC in clinical use. However, emerging data indicate that BRCA-deficient cancers may be resistant to PARPi, and the mechanisms of this resistance remain elusive. We found that amplification of KRAS likely underlies PARPi resistance in BRCA2-deficient HGSOC. Our data suggest that PLK1 inhibition restores sensitivity to PARPi in HGSOC with KRAS amplification. The sequential combination of PLK1 inhibitor (PLK1i) and PARPi drastically reduces HGSOC cell survival and increases apoptosis. Furthermore, we were able to show that a sequential combination of PLK1i and PARPi enhanced the cellular apoptotic response to carboplatin-based chemotherapy in KRAS-amplified resistant HGSOC cells and 3D spheroids derived from recurrent ovarian cancer patients. Our results shed new light on the critical role of PLK1 in reversing PARPi resistance in KRAS-amplified HGSOC, and offer a new therapeutic strategy for this class of ovarian cancer patients where only limited options currently exist.

Keywords: BRCA2 deficiency; DNA damage; KRAS amplification; PARP inhibitor resistance; PLK1-based combinatorial therapy; high-grade serous ovarian cancer

DOI: https://doi.org/10.3390/ijms231810892

Cancers (Basel). 2022 Sep 06. pii: 4344. [Epub ahead of print]14(18):

Prognostic and Predictive Role of Tumor-Infiltrating Lymphocytes (TILs) in Ovarian Cancer.

Daniele Fanale, Alessandra Dimino, Erika Pedone, Chiara Brando, Lidia Rita Corsini, Clarissa Filorizzo, Alessia Fiorino, Maria Chiara Lisanti, Luigi Magrin, Ugo Randazzo, Tancredi Didier Bazan Russo, Antonio Russo, Viviana Bazan.

In the last decade, tumor-infiltrating lymphocytes (TILs) have been recognized as clinically relevant prognostic markers for improved survival, providing the immunological basis for the development of new therapeutic strategies and showing a significant prognostic and predictive role in several malignancies, including ovarian cancer (OC). In fact, many OCs show TILs whose typology and degree of infiltration have been shown to be strongly correlated with prognosis and survival. The OC histological subtype with the higher presence of TILs is the high-grade serous carcinoma (HGSC) followed by the endometrioid subtype, whereas mucinous and clear cell OCs seem to contain a lower percentage of TILs. The abundant presence of TILs in OC suggests an immunogenic potential for this tumor. Despite the high immunogenic potential, OC has been described as a highly immunosuppressive tumor with a high expression of PD1 by TILs. Although further studies are needed to better define their role in prognostic stratification and the therapeutic implication, intraepithelial TILs represent a relevant prognostic factor to take into account in OC. In this review, we will discuss the promising role of TILs as markers which are able to reflect the anticancer immune response, describing their potential capability to predict prognosis and therapy response in OC.

Keywords: ovarian cancer; prognostic and predictive role; tumor immunology; tumor microenvironment; tumor-infiltrating lymphocytes (TILs)

DOI: https://doi.org/10.3390/cancers14184344

Clin Lab Med. 2022 Sep;pii: S0272-2712(22)00032-4. [Epub ahead of print]42(3): 451-468

Copy Number Analysis in Cancer Diagnostic Testing.

Tara Spence, Adrian M Dubuc.

Accurate detection of copy number alterations (CNAs) has become increasingly important in clinical oncology for the purpose of diagnosis, prognostication, and disease management. Cytogenetic approaches for the detection of CNAs, including karyotype, fluorescence in situ hybridization (FISH), and chromosomal microarray, remain mainstays in clinical laboratories. Yet, with rapidly decreasing costs and improved accuracy of CNA detection using emerging technologies such as next-generation sequencing and optical genome mapping, we are approaching a new era of cytogenomics and molecular oncology. The aim of this review is to describe the benefits and limitations associated with the routine clinical application of available classic, emerging, and projected future technologies for the detection of CNAs in oncology.

Keywords: Clinical oncology; Copy number analysis; Cytogenomics; Genome diagnostics

DOI: https://doi.org/10.1016/j.cll.2022.05.003

Comput Struct Biotechnol J. 2022 ;20 4870-4884

Computational solutions for spatial transcriptomics.

Iivari Kleino, Paulina Frolovaitė, Tomi Suomi, Laura L Elo.

Transcriptome level expression data connected to the spatial organization of the cells and molecules would allow a comprehensive understanding of how gene expression is connected to the structure and function in the biological systems. The spatial transcriptomics platforms may soon provide such information. However, the current platforms still lack spatial resolution, capture only a fraction of the transcriptome heterogeneity, or lack the throughput for large scale studies. The strengths and weaknesses in current ST platforms and computational solutions need to be taken into account when planning spatial transcriptomics studies. The basis of the computational ST analysis is the solutions developed for single-cell RNA-sequencing data, with advancements taking into account the spatial connectedness of the transcriptomes. The scRNA-seq tools are modified for spatial transcriptomics or new solutions like deep learning-based joint analysis of expression, spatial, and image data are developed to extract biological information in the spatially resolved transcriptomes. The computational ST analysis can reveal remarkable biological insights into spatial patterns of gene expression, cell signaling, and cell type variations in connection with cell type-specific signaling and organization in complex tissues. This review covers the topics that help choosing the platform and computational solutions for spatial transcriptomics research. We focus on the currently available ST methods and platforms and their strengths and limitations. Of the computational solutions, we provide an overview of the analysis steps and tools used in the ST data analysis. The compatibility with the data types and the tools provided by the current ST analysis frameworks are summarized.

Keywords: AOI, area of illumination; BICCN, Brain Initiative Cell Census Network; BOLORAMIS, barcoded oligonucleotides ligated on RNA amplified for multiplexed and parallel in situ analyses; Baysor, Bayesian Segmentation of Spatial Transcriptomics Data; BinSpect, Binary Spatial Extraction; CCC, cell–cell communication; CCI, cell–cell interactions; CNV, copy-number variation; Computational biology; DSP, digital spatial profiling; DbiT-Seq, Deterministic Barcoding in Tissue for spatial omics sequencing; FA, factor analysis; FFPE, formalin-fixed, paraffin-embedded; FISH, fluorescence in situ hybridization; FISSEQ, fluorescence in situ sequencing of RNA; FOV, Field of view; GRNs, gene regulation networks; GSEA, gene set enrichment analysis; GSVA, gene set variation analysis; HDST, high definition spatial transcriptomics; HMRF, hidden Markov random field; ICG, interaction changed genes; ISH, in situ hybridization; ISS, in situ sequencing; JSTA, Joint cell segmentation and cell type annotation; KNN, k-nearest neighbor; LCM, Laser Capture Microdissection; LCM-seq, laser capture microdissection coupled with RNA sequencing; LOH, loss of heterozygosity analysis; MC, Molecular Cartography; MERFISH, multiplexed error-robust FISH; NMF (NNMF), Non-negative matrix factorization; PCA, Principal Component Analysis; PIXEL-seq, Polony (or DNA cluster)-indexed library-sequencing; PL-lig, padlock ligation; QC, quality control; RNAseq, RNA sequencing; ROI, region of interest; SCENIC, Single-Cell rEgulatory Network Inference and Clustering; SME, Spatial Morphological gene Expression normalization; SPATA, SPAtial Transcriptomic Analysis; ST Pipeline, Spatial Transcriptomics Pipeline; ST, Spatial transcriptomics; STARmap, spatially-resolved transcript amplicon readout mapping; Single-cell analysis; Spatial data analysis frameworks; Spatial deconvolution; Spatial transcriptomics; TIVA, Transcriptome in Vivo Analysis; TMA, tissue microarray; TME, tumor micro environment; UMAP, Uniform Manifold Approximation and Projection for Dimension Reduction; UMI, unique molecular identifier; ZipSeq, zipcoded sequencing.; scRNA-seq, single-cell RNA sequencing; scvi-tools, single-cell variational inference tools; seqFISH, sequential fluorescence in situ hybridization; sequ-smFISH, sequential single-molecule fluorescent in situ hybridization; smFISH, single molecule FISH; t-SNE, t-distributed stochastic neighbor embedding

DOI: https://doi.org/10.1016/j.csbj.2022.08.043

Gynecol Oncol. 2022 Sep 15. pii: S0090-8258(22)00590-X. [Epub ahead of print]

Circulating tumor DNA monitoring for early recurrence detection in epithelial ovarian cancer.

OBJECTIVE: Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy. We examined the utility of circulating tumor DNA (ctDNA) as a prognostic biomarker for EOC by assessing its relationship with patient outcome and CA-125, pre-surgically and during post-treatment surveillance.
METHODS: Plasma samples were collected from patients with stage I-IV EOC. Cohort A included patients with pre-surgical samples (N = 44, median follow-up: 2.7 years), cohort B and C included: patients with serially collected post-surgically (N = 12) and, during surveillance (N = 13), respectively (median follow-up: 2 years). Plasma samples were analyzed using a tumor-informed, personalized multiplex-PCR NGS assay; ctDNA status and CA-125 levels were correlated with clinical features and outcomes.
RESULTS: Genomic profiling was performed on the entire cohort and was consistent with that seen in TCGA. In cohort A, ctDNA-positivity was observed in 73% (32/44) of presurgical samples and was higher in high nuclear grade disease. In cohort B and C, ctDNA was only detected in patients who relapsed (100% sensitivity and specificity) and preceded radiological findings by an average of 10 months. The presence of ctDNA at a single timepoint after completion of surgery +/- adjuvant chemotherapy and serially during surveillance was a strong predictor of relapse (HR:17.6, p = 0.001 and p < 0.0001, respectively), while CA-125 positivity was not (p = 0.113 and p = 0.056).
CONCLUSIONS: The presence of ctDNA post-surgically is highly prognostic of reduced recurrence-free survival. CtDNA outperformed CA-125 in identifying patients at highest risk of recurrence. These results suggest that monitoring ctDNA could be beneficial in clinical decision-making for EOC patients.

Keywords: CA-125; Epithelial ovarian cancer; Prognostic; Tumor biomarkers; ctDNA

DOI: https://doi.org/10.1016/j.ygyno.2022.09.004