bims-tumhet 2022-10-09 papers

Issue of 2022–10–09
five papers selected by
Sergio Marchini, Humanitas Research

J Mol Diagn. 2022 Sep 30. pii: S1525-1578(22)00266-5. [Epub ahead of print]

Homologous recombination deficiency (HRD) as an ovarian cancer biomarker in a real-world cohort - validation of decentralized genomic profiling.

The diagnostic evaluation of homologous recombination deficiency (HRD) is central to define targeted therapy strategies for patients with ovarian carcinoma. In this project, we evaluated HRD in 514 ovarian carcinoma samples by next-generation sequencing of DNA libraries including biotinylated probes covering BRCA1/BRCA2 and 26,523 SNPs using the standardized Myriad HRD assay, with the predefined cutpoint of ≥42 for a positive genomic instability score (GIS). All samples were measured in the central Myriad laboratory and in an academic molecular pathology laboratory.A positive GIS was detected in 196 (38.1%) of tumors, while 318 (61.9%) were GIS-negative. Combining GIS and BRCA-mutations, a total of 200 (38.9%) of the 514 tumors were HRD-positive. A positive GIS was significantly associated with high-grade serous histology (p<0.000001), grade 3 tumors (p=0.001) and patient age <60 years (p=0.0003). The concordance between both laboratories for the GIS-status was 96.9% (p<0.000001) with a sensitivity of 94.6% and a specificity of 98.4%. Concordance for HRD-status was 97.1% (499 of 514 tumors).The percentage of HRD-positive tumors in our real-life cohort was similar to the proportion observed in the recently published PAOLA-1 trial, with a high concordance between central and local laboratories. Our results support introduction of the standardized HRD assay in academic molecular pathology laboratories, thus broadening the access to personalized oncology strategies for patients with ovarian cancer worldwide.

Keywords: BRCA; PARP inhibitors; homologous recombination deficiency; ovarian cancer

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

Epigenomics. 2022 Oct 05.

A novel subtype to predict prognosis and treatment response with DNA driver methylation-transcription in ovarian cancer.

Zhenyi Xu, Liuchao Zhang, Meng Wang, Yue Huang, Min Zhang, Shuang Li, Liuying Wang, Kang Li, Yan Hou.

Aims: To identify a novel subtype with DNA driver methylation-transcriptomic multiomics and predict prognosis and therapy response in serous ovarian cancer (SOC). Methods: SOC cohorts with both mRNA and methylation were collected, and DNA driver methylation (DNAme) was identified with the MithSig method. A novel prognostic subtype was developed by integrating the information on DNAme and prognosis-regulated DNAme-associated mRNA by similarity network fusion. Results: 43 overlapped DNAme were identified in three independent cohorts. SOC patients were categorized into three distinct subtypes by integrated multiomics. There were differences in prognosis, tumor microenvironment and response to therapy among the subtypes. Conclusion: This study identified 43 DNAmes and proposes a novel subtype toward personalized chemotherapy and immunotherapy for SOC patients based on multiomics.

Keywords: DNA driver methylation; heterogeneity; multiomics integration; personalized therapy; serous ovarian cancer

DOI: https://doi.org/10.2217/epi-2022-0206

Mol Cancer Ther. 2022 Oct 05. pii: MCT-22-0004. [Epub ahead of print]

NOTCH signaling limits the response of Low Grade Serous Ovarian Cancers to MEK inhibition.

Low-grade serous ovarian cancer (LGSOC) is a rare subtype of epithelial ovarian cancer with high fatality rates in advanced stages due to its chemo-resistant properties. LGSOC is characterized by activation of MAPK signaling and recent clinical trials indicate that the MEK inhibitor (MEKi) trametinib may be a good treatment option for a subset of patients. Understanding MEKi resistance mechanisms and subsequent identification of rational drug combinations to suppress resistance may greatly improve LGSOC treatment strategies. Both gain-of-function and loss-of-function CRISPR-Cas9 genome-wide libraries were used to screen LGSOC cell lines to identify genes that modulate the response to MEKi. Overexpression of MAML2 and loss of MAP3K1 were identified, both leading to overexpression of the NOTCH target HES1, which has a causal role in this process as its knockdown reversed MEKi resistance. Interestingly, increased HES1 expression was also observed in selected spontaneous trametinib resistant clones, next to activating MAP2K1 (MEK1) mutations. Subsequent trametinib synthetic lethality screens identified SHOC2 downregulation as being synthetic lethal with MEKi. Targeting SHOC2 with pan-RAF inhibitors (pan-RAFi) in combination with MEKi was effective in parental LGSOC cell lines, in MEKi resistant derivatives, in primary ascites cultures from LGSOC patients and in LGSOC (cell line derived and patient-derived) xenograft mouse models. We found that the combination of pan-RAFi with MEKi downregulated HES1 levels in trametinib resistant cells, providing an explanation for the synergy that was observed. Combining MEKi with pan-RAFi may provide a promising treatment strategy for LGSOC patients, which warrants further clinical validation.

DOI: https://doi.org/10.1158/1535-7163.MCT-22-0004

Cancer Res. 2022 Oct 07. pii: CAN-22-1620. [Epub ahead of print]

Spatial transcriptomic analysis of ovarian cancer precursors reveals reactivation of IGFBP2 during pathogenesis.

Yeh Wang, Peng Huang, Brant G Wang, Tricia Murdock, Leslie Cope, Fang-Chi Hsu, Tian-Li Wang, Ie-Ming Shih.

Elucidating the earliest pathogenic steps in cancer development is fundamental to improving its early detection and prevention. Ovarian high-grade serous carcinoma, a highly aggressive cancer, originates from the fallopian tube epithelium through a precursor stage, serous tubal intraepithelial carcinoma (STIC). In this study, we performed spatial transcriptomic analysis to compare STICs, carcinoma, and their matched normal fallopian tube. Several differentially expressed genes in STICs and carcinomas were involved in cancer metabolism and detected in a larger independent transcriptomic dataset of ovarian high-grade serous carcinomas. Among these, insulin-like growth factor binding protein-2 (IGFBP2) was found to undergo DNA hypomethylation and be increased at the protein level in STICs. Pyrosequencing revealed an association of IGFBP2 expression with the methylation state of its proximal enhancer, and 5-azacytidine treatment increased IGFBP2 expression. In postmenopausal fallopian tubes where most STICs are detected, IGFBP2 immunoreactivity was detected in all 38 proliferatively active STICs but was undetectable in morphologically normal tubal epithelia, including those with TP53 mutations. In premenopausal fallopian tubes, IGFBP2 expression was limited to the secretory epithelium at the proliferative phase, and estradiol treatment increased IGFBP2 expression levels. IGFBP2 knockdown suppressed the growth of IGFBP2-expressing tubal epithelial cells via inactivation of the AKT pathway. Taken together, demethylation of the proximal enhancer of IGFBP2 drives tumor development by maintaining the increased IGFBP2 required for proliferation in an otherwise estrogen-deprived, proliferation-quiescent, and postmenopausal tubal microenvironment.

DOI: https://doi.org/10.1158/0008-5472.CAN-22-1620

Nat Biotechnol. 2022 Oct 03.

The expanding vistas of spatial transcriptomics.

Luyi Tian, Fei Chen, Evan Z Macosko.

The formation and maintenance of tissue integrity requires complex, coordinated activities by thousands of genes and their encoded products. Until recently, transcript levels could only be quantified for a few genes in tissues, but advances in DNA sequencing, oligonucleotide synthesis and fluorescence microscopy have enabled the invention of a suite of spatial transcriptomics technologies capable of measuring the expression of many, or all, genes in situ. These technologies have evolved rapidly in sensitivity, multiplexing and throughput. As such, they have enabled the determination of the cell-type architecture of tissues, the querying of cell-cell interactions and the monitoring of molecular interactions between tissue components. The rapidly evolving spatial genomics landscape will enable generalized high-throughput genomic measurements and perturbations to be performed in the context of tissues. These advances will empower hypothesis generation and biological discovery and bridge the worlds of tissue biology and genomics.

DOI: https://doi.org/10.1038/s41587-022-01448-2