bims-tumhet 2021-06-20 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2021–06–20
thirteen papers selected by
Sergio Marchini, Humanitas Research

Deep learning for diagnosis and survival prediction in soft tissue sarcoma.
Appropriate use of cancer comprehensive genome profiling assay using circulating tumor DNA.
Enhanced specificity of clinical high-sensitivity tumor mutation profiling in cell-free DNA via paired normal sequencing using MSK-ACCESS.
Immunological Significance of Prognostic DNA Methylation Sites in Hepatocellular Carcinoma.
kataegis: an R package for identification and visualization of the genomic localized hypermutation regions using high-throughput sequencing.
TMB cutoffs fail to predict benefit of PD-1 blockade in gastroesophageal adenocarcinoma in Keynote-061.
Tumor Genotyping and Homologous Recombination Repair Gene Variants in Patients With Epithelial Ovarian Cancer: Is Pathogenic Enough?
Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation.
A DNA methylation-based liquid biopsy for triple-negative breast cancer.
Navigating the DNA methylation landscape of cancer.
Complementary role of circulating tumor DNA assessment and tissue genomic profiling in metastatic renal cell carcinoma.
Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA.
STING pathway expression in low-grade serous carcinoma of the ovary: an unexpected therapeutic opportunity?

Ann Oncol. 2021 Jun 14. pii: S0923-7534(21)02055-X. [Epub ahead of print]

Deep learning for diagnosis and survival prediction in soft tissue sarcoma.

S Foersch, M Eckstein, D-C Wagner, F Gach, A-C Woerl, J Geiger, C Glasner, S Schelbert, S Schulz, S Porubsky, A Kreft, A Hartmann, A Agaimy, W Roth.

   BACKGROUND: Clinical management of soft tissue sarcoma (STS) is particularly challenging. Here, we used digital pathology and deep learning (DL) for diagnosis and prognosis prediction of STS.
PATIENTS AND METHODS: Our retrospective, multi-center study included a total of 506 histopathological slides from 291 patients with STS. The TCGA cohort (240 patients) served as training and validation set. A second, multicenter cohort (51 patients) served as an additional test set. The use of the DL model as a clinical decision support system was evaluated by 9 pathologists with different levels of expertise. For prognosis prediction, 139 slides from 85 patients with leiomyosarcoma (LMS) were used. Area under the receiver operating characteristic (AUROC) and accuracy served as main outcome measures.
RESULTS: The DL model achieved a mean AUROC of 0.97 (±0.01) and an accuracy of 79.9% (±6.1%) in diagnosing the five most common STS subtypes. The DL model significantly improved the accuracy of the pathologists from 46.3% (±15.5%) to 87.1% (±11.1%). Furthermore, they were significantly faster and more certain in their diagnosis. In leiomyosarcoma (LMS), the mean AUROC in predicting the disease-specific survival status was 0.91 (±0.1) and the accuracy was 88.9% (±9.9%). Cox regression showed the DL model's prediction to be a significant independent prognostic factor (p=0.008, HR 5.5, 95% CI 1.56-19.7) in these patients, outperforming other risk factors.
CONCLUSION(S): DL can be used to accurately diagnose frequent subtypes of STS from conventional histopathological slides. It might be used for prognosis prediction in LMS, the most prevalent STS subtype in our cohort. It can also help pathologists to make faster and more accurate diagnoses. This could substantially improve the clinical management of STS patients.

Keywords:  Artificial Intelligence; Clinical Decision Support System; Deep Learning; Digital Pathology; Prognosis Prediction; Soft Tissue Sarcoma

DOI:  https://doi.org/10.1016/j.annonc.2021.06.007
Cancer Sci. 2021 Jun 15.

Appropriate use of cancer comprehensive genome profiling assay using circulating tumor DNA.

Working Group of a Joint Task Force of Three Academic Societies for the Promotion of Cancer Genomic Medicine

  Comprehensive genomic profiling (CGP) is increasingly used for the routine clinical management of solid cancer. In July 2018, the use of tumor tissue-based CGP assays became available for all solid cancers under the universal health insurance system in Japan. Several restrictions presently exist, such as patient eligibility and limitations on the opportunities to perform such assays. The clinical implementation of CGP based on plasma circulating tumor DNA (ctDNA) is also expected to raise issues regarding the selection and use of tissue DNA and ctDNA CGP. A Joint Task Force for the Promotion of Cancer Genome Medicine comprised of three Japanese cancer-related societies has formulated a policy proposal for the appropriate use of plasma CGP (in Japanese), available at https://www.jca.gr.jp/researcher/topics/2021/files/20210120.pdf, http://www.jsco.or.jp/jpn/user_data/upload/File/20210120.pdf, and https://www.jsmo.or.jp/file/dl/newsj/2765.pdf. Based on these recommendations, the working group has summarized the respective advantages and cautions regarding the use of tissue DNA CGP and ctDNA CGP with reference to the advice of a multidisciplinary expert panel, the preferred use of plasma specimens over tissue, and multiple ctDNA testing. These recommendations have been prepared to maximize the benefits of performing CGP assays and might be applicable in other countries and regions.

Keywords:  cancer comprehensive genome profiling assay; circulating tumor DNA; liquid biopsy; next-generation sequencer; plasma

DOI:  https://doi.org/10.1111/cas.15022
Nat Commun. 2021 Jun 18. 12(1): 3770

Enhanced specificity of clinical high-sensitivity tumor mutation profiling in cell-free DNA via paired normal sequencing using MSK-ACCESS.

A Rose Brannon, Gowtham Jayakumaran, Monica Diosdado, Juber Patel, Anna Razumova, Yu Hu, Fanli Meng, Mohammad Haque, Justyna Sadowska, Brian J Murphy, Tessara Baldi, Ian Johnson, Ryan Ptashkin, Maysun Hasan, Preethi Srinivasan, Anoop Balakrishnan Rema, Ivelise Rijo, Aaron Agarunov, Helen Won, Dilmi Perera, David N Brown, Aliaksandra Samoila, Xiaohong Jing, Erika Gedvilaite, Julie L Yang, Dennis P Stephens, Jenna-Marie Dix, Nicole DeGroat, Khedoudja Nafa, Aijazuddin Syed, Alan Li, Emily S Lebow, Anita S Bowman, Donna C Ferguson, Ying Liu, Douglas A Mata, Rohit Sharma, Soo-Ryum Yang, Tejus Bale, Jamal K Benhamida, Jason C Chang, Snjezana Dogan, Meera R Hameed, Jaclyn F Hechtman, Christine Moung, Dara S Ross, Efsevia Vakiani, Chad M Vanderbilt, JinJuan Yao, Pedram Razavi, Lillian M Smyth, Sarat Chandarlapaty, Gopa Iyer, Wassim Abida, James J Harding, Benjamin Krantz, Eileen O'Reilly, Helena A Yu, Bob T Li, Charles M Rudin, Luis Diaz, David B Solit, Maria E Arcila, Marc Ladanyi, Brian Loomis, Dana Tsui, Michael F Berger, Ahmet Zehir, Ryma Benayed.

Circulating cell-free DNA from blood plasma of cancer patients can be used to non-invasively interrogate somatic tumor alterations. Here we develop MSK-ACCESS (Memorial Sloan Kettering - Analysis of Circulating cfDNA to Examine Somatic Status), an NGS assay for detection of very low frequency somatic alterations in 129 genes. Analytical validation demonstrated 92% sensitivity in de-novo mutation calling down to 0.5% allele frequency and 99% for a priori mutation profiling. To evaluate the performance of MSK-ACCESS, we report results from 681 prospective blood samples that underwent clinical analysis to guide patient management. Somatic alterations are detected in 73% of the samples, 56% of which have clinically actionable alterations. The utilization of matched normal sequencing allows retention of somatic alterations while removing over 10,000 germline and clonal hematopoiesis variants. Our experience illustrates the importance of analyzing matched normal samples when interpreting cfDNA results and highlights the importance of cfDNA as a genomic profiling source for cancer patients.

DOI: https://doi.org/10.1038/s41467-021-24109-5
Front Mol Biosci. 2021 ;8 683240

Immunological Significance of Prognostic DNA Methylation Sites in Hepatocellular Carcinoma.

Qianhui Xu, Yuanbo Hu, Shaohuai Chen, Yulun Zhu, Siwei Li, Feng Shen, Yifan Guo, Tao Sun, Xiaoyu Chen, Jinpeng Jiang, Wen Huang.

  Background: Hepatocellular carcinoma (HCC) is a tumor with high morbidity and high mortality worldwide. DNA methylation, one of the most common epigenetic changes, might serve a vital regulatory role in cancer. Methods: To identify categories based on DNA methylation data, consensus clustering was employed. The risk signature was yielded by systematic bioinformatics analyses based on the remarkably methylated CpG sites of cluster 1. Kaplan-Meier analysis, variable regression analysis, and ROC curve analysis were further conducted to validate the prognosis predictive ability of risk signature. Gene set enrichment analysis (GSEA) was performed for functional annotation. To uncover the context of tumor immune microenvironment (TIME) of HCC, we employed the ssGSEA algorithm and CIBERSORT method and performed TIMER database exploration and single-cell RNA sequencing analysis. Additionally, quantitative real-time polymerase chain reaction was employed to determine the LRRC41 expression and preliminarily explore the latent role of LRRC41 in prognostic prediction. Finally, mutation data were analyzed by employing the "maftools" package to delineate the tumor mutation burden (TMB). Results: HCC samples were assigned into seven subtypes with different overall survival and methylation levels based on 5'-cytosine-phosphate-guanine-3' (CpG) sites. The risk prognostic signature including two candidate genes (LRRC41 and KIAA1429) exhibited robust prognostic predictive accuracy, which was validated in the external testing cohort. Then, the risk score was significantly correlated with the TIME and immune checkpoint blockade (ICB)-related genes. Besides, a prognostic nomogram based on the risk score and clinical stage presented powerful prognostic ability. Additionally, LRRC41 with prognostic value was corroborated to be closely associated with TIME characterization in both expression and methylation levels. Subsequently, the correlation regulatory network uncovered the potential targets of LRRC41 and KIAA1429. Finally, the methylation level of KIAA1429 was correlated with gene mutation status. Conclusion: In summary, this is the first to identify HCC samples into distinct clusters according to DNA methylation and yield the CpG-based prognostic signature and quantitative nomogram to precisely predict prognosis. And the pivotal player of DNA methylation of genes in the TIME and TMB status was explored, contributing to clinical decision-making and personalized prognosis monitoring of HCC.

Keywords:  DNA methylation sites; hepatocellular carcinoma; immune checkpoint blockade; prognosis; tumor immune environment; tumor mutation burden

DOI:  https://doi.org/10.3389/fmolb.2021.683240
BMC Genomics. 2021 Jun 12. 22(1): 440

kataegis: an R package for identification and visualization of the genomic localized hypermutation regions using high-throughput sequencing.

Xue Lin, Yingying Hua, Shuanglin Gu, Li Lv, Xingyu Li, Pin Chen, Peng Dai, Yunyun Hu, Anna Liu, Jian Li.

   BACKGROUND: Genomic localized hypermutation regions were found in cancers, which were reported to be related to the prognosis of cancers. This genomic localized hypermutation is quite different from the usual somatic mutations in the frequency of occurrence and genomic density. It is like a mutations "violent storm", which is just what the Greek word "kataegis" means.
RESULTS: There are needs for a light-weighted and simple-to-use toolkit to identify and visualize the localized hypermutation regions in genome. Thus we developed the R package "kataegis" to meet these needs. The package used only three steps to identify the genomic hypermutation regions, i.e., i) read in the variation files in standard formats; ii) calculate the inter-mutational distances; iii) identify the hypermutation regions with appropriate parameters, and finally one step to visualize the nucleotide contents and spectra of both the foci and flanking regions, and the genomic landscape of these regions.
CONCLUSIONS: The kataegis package is available on Bionconductor/Github ( https://github.com/flosalbizziae/kataegis ), which provides a light-weighted and simple-to-use toolkit for quickly identifying and visualizing the genomic hypermuation regions.

Keywords:  High-throughput sequencing; Kataegis; R; Visualization

DOI:  https://doi.org/10.1186/s12864-021-07696-x
Ann Oncol. 2021 Jun 14. pii: S0923-7534(21)02054-8. [Epub ahead of print]

TMB cutoffs fail to predict benefit of PD-1 blockade in gastroesophageal adenocarcinoma in Keynote-061.

M B Foote, S B Maron, A Cercek, G Argiles, B Rousseau, L A Diaz.

DOI: https://doi.org/10.1016/j.annonc.2021.06.006
Front Oncol. 2021 ;11 683057

Tumor Genotyping and Homologous Recombination Repair Gene Variants in Patients With Epithelial Ovarian Cancer: Is Pathogenic Enough?

Elena Fountzilas, Vassiliki Kotoula, Georgia-Angeliki Koliou, Michalis Liontos, Kyriaki Papadopoulou, Eleni Giannoulatou, Alexios Papanikolaou, Ioannis Tikas, Sofia Chrisafi, Davide Mauri, Kyriakos Chatzopoulos, Florentia Fostira, Dimitrios Pectasides, Georgios Oikonomopoulos, Dimitra Aivazi, Angeliki Andrikopoulou, Anastasios Visvikis, Gerasimos Aravantinos, Flora Zagouri, George Fountzilas.

  Our hypothesis was that the predictive accuracy of pathogenic variants in genes participating in the homologous recombination repair (HRR) system in patients with epithelial ovarian cancer (EOC) could be improved by considering additional next-generation sequencing (NGS) metrics. NGS genotyping was performed in tumor tissue, retrospectively and prospectively collected from patients with EOC, diagnosed from 8/1998 to 10/2016. Variants were considered clonal when variant allele frequencies corresponded to >25%. The primary endpoint was overall survival (OS). This study included 501 patients with EOC, predominantly with high-grade serous (75.2%) and advanced stage tumors (81.7%); median age was 58 years (22-84). Pathogenic and clonal pathogenic variants in HRR and/or TP53 genes were identified in 72.8% and 66.5% tumors, respectively. With a median follow-up of 123.9 months, the presence of either pathogenic or clonal pathogenic HRR-only variants was associated with longer OS compared to HRR/TP53 co-mutation (HR=0.54; 95% CI, 0.34-0.87, Wald's p=0.012 and HR=0.45; 95% CI, 0.27-0.78, Wald's p=0.004, respectively). However, only the presence of clonal HRR-only variants was independently associated with improved OS (HR=0.55; 95% CI, 0.32-0.94, p=0.030). Variant clonality and co-occuring TP53 variants affect the predictive value of HRR pathogenic variants for platinum agents in patients with EOC.
Clinical Trial Registration: [ClinicalTrials.gov], identifier [NCT04716374].

Keywords:  BRCA; biomarker; co-mutation; homologous recombination repair; predictive; prognostic

DOI:  https://doi.org/10.3389/fonc.2021.683057
BMC Genomics. 2021 Jun 15. 22(1): 446

Characterizing the properties of bisulfite sequencing data: maximizing power and sensitivity to identify between-group differences in DNA methylation.

Dorothea Seiler Vellame, Isabel Castanho, Aisha Dahir, Jonathan Mill, Eilis Hannon.

   BACKGROUND: The combination of sodium bisulfite treatment with highly-parallel sequencing is a common method for quantifying DNA methylation across the genome. The power to detect between-group differences in DNA methylation using bisulfite-sequencing approaches is influenced by both experimental (e.g. read depth, missing data and sample size) and biological (e.g. mean level of DNA methylation and difference between groups) parameters. There is, however, no consensus about the optimal thresholds for filtering bisulfite sequencing data with implications for the reproducibility of findings in epigenetic epidemiology.
RESULTS: We used a large reduced representation bisulfite sequencing (RRBS) dataset to assess the distribution of read depth across DNA methylation sites and the extent of missing data. To investigate how various study variables influence power to identify DNA methylation differences between groups, we developed a framework for simulating bisulfite sequencing data. As expected, sequencing read depth, group size, and the magnitude of DNA methylation difference between groups all impacted upon statistical power. The influence on power was not dependent on one specific parameter, but reflected the combination of study-specific variables. As a resource to the community, we have developed a tool, POWEREDBiSeq, which utilizes our simulation framework to predict study-specific power for the identification of DNAm differences between groups, taking into account user-defined read depth filtering parameters and the minimum sample size per group.
CONCLUSIONS: Our data-driven approach highlights the importance of filtering bisulfite-sequencing data by minimum read depth and illustrates how the choice of threshold is influenced by the specific study design and the expected differences between groups being compared. The POWEREDBiSeq tool, which can be applied to different types of bisulfite sequencing data (e.g. RRBS, whole genome bisulfite sequencing (WGBS), targeted bisulfite sequencing and amplicon-based bisulfite sequencing), can help users identify the level of data filtering needed to optimize power and aims to improve the reproducibility of bisulfite sequencing studies.

Keywords:  Bisulfite sequencing; DNA methylation; Epigenetics; Power; RRBS; Read depth; Sample size

DOI:  https://doi.org/10.1186/s12864-021-07721-z
NPJ Precis Oncol. 2021 Jun 16. 5(1): 53

A DNA methylation-based liquid biopsy for triple-negative breast cancer.

Katrina Cristall, Francois-Clement Bidard, Jean-Yves Pierga, Michael J Rauh, Tatiana Popova, Clara Sebbag, Olivier Lantz, Marc-Henri Stern, Christopher R Mueller.

Here, we present a next-generation sequencing (NGS) methylation-based blood test called methylation DETEction of Circulating Tumour DNA (mDETECT) designed for the optimal detection and monitoring of metastatic triple-negative breast cancer (TNBC). Based on a highly multiplexed targeted sequencing approach, this assay incorporates features that offer superior performance and included 53 amplicons from 47 regions. Analysis of a previously characterised cohort of women with metastatic TNBC with limited quantities of plasma (<2 ml) produced an AUC of 0.92 for detection of a tumour with a sensitivity of 76% for a specificity of 100%. mDETECTTNBC was quantitative and showed superior performance to an NGS TP53 mutation-based test carried out on the same patients and to the conventional CA15-3 biomarker. mDETECT also functioned well in serum samples from metastatic TNBC patients where it produced an AUC of 0.97 for detection of a tumour with a sensitivity of 93% for a specificity of 100%. An assay for BRCA1 promoter methylation was also incorporated into the mDETECT assay and functioned well but its clinical significance is currently unclear. Clonal Hematopoiesis of Indeterminate Potential was investigated as a source of background in control subjects but was not seen to be significant, though a link to adiposity may be relevant. The mDETECTTNBC assay is a liquid biopsy able to quantitatively detect all TNBC cancers and has the potential to improve the management of patients with this disease.

DOI: https://doi.org/10.1038/s41698-021-00198-9
Trends Genet. 2021 Jun 10. pii: S0168-9525(21)00130-X. [Epub ahead of print]

Navigating the DNA methylation landscape of cancer.

Atsuya Nishiyama, Makoto Nakanishi.

  DNA methylation is a chemical modification that defines cell type and lineage through the control of gene expression and genome stability. Disruption of DNA methylation control mechanisms causes a variety of diseases, including cancer. Cancer cells are characterized by aberrant DNA methylation (i.e., genome-wide hypomethylation and site-specific hypermethylation), mainly targeting CpG islands in gene expression regulatory elements. In particular, the early findings that a variety of tumor suppressor genes (TSGs) are targets of DNA hypermethylation in cancer led to the proposal of a model in which aberrant DNA methylation promotes cellular oncogenesis through TSGs silencing. However, recent genome-wide analyses have revealed that this classical model needs to be reconsidered. In this review, we will discuss the molecular mechanisms of DNA methylation abnormalities in cancer as well as their therapeutic potential.

Keywords:  DNA methylation; DNA methyltransferase; cancer; histone modification

DOI:  https://doi.org/10.1016/j.tig.2021.05.002
Clin Cancer Res. 2021 Jun 15. pii: clincanres.0572.2021. [Epub ahead of print]

Complementary role of circulating tumor DNA assessment and tissue genomic profiling in metastatic renal cell carcinoma.

Zeynep B Zengin, Caroline Weipert, Nicholas J Salgia, Nazli Dizman, Joann Hsu, Luis Meza, Alexander Chehrazi-Raffle, Ramya Muddasani, Sabrina Salgia, Jasnoor Malhotra, Neal Chawla, Errol J Philip, Lesli Kiedrowski, Benjamin L Maughan, Nityam Rathi, Divyam Goel, Toni K Choueiri, Neeraj Agarwal, Sumanta K Pal.

PURPOSE: The role of circulating cell-free tumor DNA (ctDNA) as an adjunct to tissue genomic profiling is poorly defined in metastatic renal cell carcinoma (mRCC). In this study we aim to validate previous findings related to genomic alteration (GA) frequency in ctDNA and determine the concordance between ctDNA and tissue-based profiling in patients with mRCC.
EXPERIMENTAL DESIGN: Results of 839 mRCC patients who had ctDNA assessment with a CLIA-certified ctDNA assay between November 2016 and December 2019 were collected. Tissue-based genomic profiling was collected when available and concordance analysis between blood- and tissue-based testing was performed.
RESULTS: ctDNA was assessed in 839 patients (comprising 920 samples) with mRCC. GAs were detected in 661 samples (71.8%). Tissue-based GAs were assessed in 112 patients. Limiting our analyses to a common 73-/74-gene set and excluding samples with no ctDNA detected, a total of 228 mutations were found in tissue and blood. 34.7% (42/121) of the mutations identified in tissue were also identified via ctDNA, while 28.2% (42/149) of the mutations identified in liquid were also identified via tissue. Concordance between ctDNA and tissue-based profiling was inversely related to the time elapsed between these assays.
CONCLUSIONS: This study confirms the feasibility of ctDNA profiling in the largest mRCC cohort to date, with ctDNA identifying multiple actionable alterations. It also demonstrates that ctDNA and tissue-based genomic profiling are complementary, with both platforms identifying unique alterations, and confirms that the frequency of unique alterations increases with greater temporal separation between tests.

DOI: https://doi.org/10.1158/1078-0432.CCR-21-0572
Genome Res. 2021 Jun 17.

Enzymatic methyl sequencing detects DNA methylation at single-base resolution from picograms of DNA.

Romualdas Vaisvila, V K Chaithanya Ponnaluri, Zhiyi Sun, Bradley W Langhorst, Lana Saleh, Shengxi Guan, Nan Dai, Matthew A Campbell, Brittany S Sexton, Katherine Marks, Mala Samaranayake, James C Samuelson, Heidi E Church, Esta Tamanaha, Ivan R Corrêa, Sriharsa Pradhan, Eileen T Dimalanta, Thomas C Evans, Louise Williams, Theodore B Davis.

Bisulfite sequencing detects 5mC and 5hmC at single-base resolution. However, bisulfite treatment damages DNA, which results in fragmentation, DNA loss, and biased sequencing data. To overcome these problems, enzymatic methyl-seq (EM-seq) was developed. This method detects 5mC and 5hmC using two sets of enzymatic reactions. In the first reaction, TET2 and T4-BGT convert 5mC and 5hmC into products that cannot be deaminated by APOBEC3A. In the second reaction, APOBEC3A deaminates unmodified cytosines by converting them to uracils. Therefore, these three enzymes enable the identification of 5mC and 5hmC. EM-seq libraries were compared with bisulfite-converted DNA, and each library type was ligated to Illumina adaptors before conversion. Libraries were made using NA12878 genomic DNA, cell-free DNA, and FFPE DNA over a range of DNA inputs. The 5mC and 5hmC detected in EM-seq libraries were similar to those of bisulfite libraries. However, libraries made using EM-seq outperformed bisulfite-converted libraries in all specific measures examined (coverage, duplication, sensitivity, etc.). EM-seq libraries displayed even GC distribution, better correlations across DNA inputs, increased numbers of CpGs within genomic features, and accuracy of cytosine methylation calls. EM-seq was effective using as little as 100 pg of DNA, and these libraries maintained the described advantages over bisulfite sequencing. EM-seq library construction, using challenging samples and lower DNA inputs, opens new avenues for research and clinical applications.

DOI: https://doi.org/10.1101/gr.266551.120
J Pathol Clin Res. 2021 Jun 17.

STING pathway expression in low-grade serous carcinoma of the ovary: an unexpected therapeutic opportunity?

Jutta Huvila, Dawn R Cochrane, Monica Ta, Christine Chow, Kendall Greening, Samuel Leung, Anthony N Karnezis, Analisa DiFeo, David G Huntsman.

  Ovarian carcinoma histotypes are distinct diseases with variable clinical outcomes and response to treatment. There is a need for new subtype-specific treatment modalities, especially for women with widespread and chemo-resistant disease. Stimulator of interferon genes (STING) is a part of the cGAS-STING pathway that mediates innate immune defence against infectious DNA-containing pathogens and also detects tumour-derived DNA and generates intrinsic antitumour immunity. The STING signalling pathway is suppressed by several mechanisms in a variety of malignant diseases and, in some cancers that may be a requirement for cellular transformation. The aim of this study was to use immunohistochemistry to evaluate STING protein expression across normal tissue, paratubal and ovarian cysts, and ovarian tumour histotypes including ovarian carcinomas. Herein, we show that the fallopian tube ciliated cells express STING protein, whereas the secretory cells are negative. STING expression differs among ovarian cancer histotypes; low-grade serous ovarian carcinomas and serous borderline tumours have uniform high STING expression, while high-grade serous and endometrioid carcinomas have heterogeneous expression, and clear cell and mucinous carcinomas show low expression. As low-grade serous carcinomas are known to be genomically stable and typically lack a prominent host immune response, the consistently high STING expression is unexpected. High STING expression may reflect pathway activation or histogenesis and the mechanisms may be different in different ovarian carcinoma histotypes. Further studies are needed to determine whether the STING signalling pathway is active and whether these tumours would be candidates for therapeutic interventions that trigger innate immunity activation.

Keywords:  STING; innate immunity; low-grade serous ovarian carcinoma

DOI:  https://doi.org/10.1002/cjp2.230