Mutations in cancer-relevant genes are ubiquitous in histologically normal endometrial tissue.

OBJECTIVE: Endometrial cancer (EndoCA) is the most common gynecologic cancer and incidence and mortality rate continue to increase. Despite well-characterized knowledge of EndoCA-defining mutations, no effective diagnostic or screening tests exist. To lay the foundation for testing development, our study focused on defining the prevalence of somatic mutations present in non-cancerous uterine tissue. METHODS: We obtained ≥8 uterine samplings, including separate endometrial and myometrial layers, from each of 22 women undergoing hysterectomy for non-cancer conditions. We ultra-deep sequenced (>2000× coverage) samples using a 125 cancer-relevant gene panel. RESULTS: All women harbored complex mutation patterns. In total, 308 somatic mutations were identified with mutant allele frequencies ranging up to 96.0%. These encompassed 56 unique mutations from 24 genes. The majority of samples possessed predicted functional cancer mutations but curiously no growth advantage over non-functional mutations was detected. Functional mutations were enriched with increasing patient age (p = 0.045) and BMI (p = 0.0007) and in endometrial versus myometrial layers (68% vs 39%, p = 0.0002). Finally, while the somatic mutation landscape shared similar mutation prevalence in key TCGA-defined EndoCA genes, notably PIK3CA, significant differences were identified, including NOTCH1 (77% vs 10%), PTEN (9% vs 61%), TP53 (0% vs 37%) and CTNNB1 (0% vs 26%). CONCLUSIONS: An important caveat for future liquid biopsy/DNA-based cancer diagnostics is the repertoire of shared and distinct mutation profiles between histologically unremarkable and EndoCA tissues. The lack of selection pressure between functional and non-functional mutations in histologically unremarkable uterine tissue may offer a glimpse into an unrecognized EndoCA protective mechanism.

Dual Inhibition of SYK and EGFR Overcomes Chemoresistance by Inhibiting CDC6 and Blocking DNA Replication.

Targeting multiple signaling pathways has been proposed as a strategy to overcome resistance to single-pathway inhibition in cancer therapy. A previous study in epithelial ovarian cancers identified hyperactivity of spleen tyrosine kinase (SYK) and epidermal growth factor receptor (EGFR), which mutually phosphorylate and activate each other. Given the potential for pharmacologic inhibition of both kinases with clinically available agents, this study aimed to assess the antitumor efficacy of both pharmacologic and genetic SYK and EGFR co-inhibition using a multifaceted approach to analyze the global phosphoproteome and chemoresistant ovarian cancer cell lines, patient-derived organoids, and xenograft models. Dual inhibition of SYK and EGFR in chemoresistant ovarian cancer cells elicited a highly synergistic antitumor effect. Notably, the combined inhibition strategy activated the DNA damage response, induced G1 cell cycle arrest, and promoted apoptosis. The phosphoproteomic analysis revealed that perturbation of SYK and EGFR signaling induced a significant reduction in both phosphorylated and total protein levels of cell division cycle 6 (CDC6), a crucial initiator of DNA replication. Together, this study offers preclinical evidence supporting dual inhibition of SYK and EGFR as a promising treatment for chemoresistant ovarian cancer that disrupts DNA synthesis by impairing formation of the prereplication complex. These findings warrant further clinical investigation to explore the potential of this combination therapy in overcoming drug resistance and improving patient outcomes.

Salpingectomy for ectopic pregnancy reduces ovarian cancer risk-a nationwide study.

Recent studies propose fallopian tubes as the tissue origin for many ovarian epithelial cancers. To further support this paradigm, we assessed whether salpingectomy for treating ectopic pregnancy had a protective effect using the Taiwan Longitudinal National Health Research Database. We identified 316 882 women with surgical treatment for ectopic pregnancy and 3 168 820 age- and index-date-matched controls from 2000 to 2016. In a nested cohort, 91.5% of cases underwent unilateral salpingectomy, suggesting that most surgically managed patients have salpingectomy. Over a follow-up period of 17 years, the ovarian carcinoma incidence was 0.0069 (95% confidence interval [CI] = 0.0060 to 0.0079) and 0.0089 (95% CI = 0.0086 to 0.0092) in the ectopic pregnancy and the control groups, respectively (P < .001). After adjusting the events to per 100 person-years, the hazard ratio (HR) in the ectopic pregnancy group was 0.70 (95% CI = 0.61 to 0.80). The risk reduction occurred only in epithelial ovarian cancer (HR = 0.73, 95% CI = 0.63 to 0.86) and not in non-epithelial subtypes. These findings show a decrease in ovarian carcinoma incidence after salpingectomy for treating ectopic pregnancy.

Single-molecule epiallelic profiling of DNA derived from routinely collected Pap specimens for noninvasive detection of ovarian cancer.

Recent advances in molecular analyses of ovarian cancer have revealed a wealth of promising tumour-specific biomarkers, including protein, DNA mutations and methylation; however, reliably detecting such alterations at satisfactorily high sensitivity and specificity through low-cost methods remains challenging, especially in early-stage diseases. Here we present PapDREAM, a new approach that enables detection of rare, ovarian-cancer-specific aberrations of DNA methylation from routinely-collected cervical Pap specimens. The PapDREAM approach employs a microfluidic platform that performs highly parallelized digital high-resolution melt to analyze locus-specific DNA methylation patterns on a molecule-by-molecule basis at or near single CpG-site resolution at a fraction (< 1/10th) of the cost of next-generation sequencing techniques. We demonstrate the feasibility of the platform by assessing intermolecular heterogeneity of DNA methylation in a panel of methylation biomarker loci using DNA derived from Pap specimens obtained from a cohort of 43 women, including 18 cases with ovarian cancer and 25 cancer-free controls. PapDREAM leverages systematic multidimensional bioinformatic analyses of locus-specific methylation heterogeneity to improve upon Pap-specimen-based detection of ovarian cancer, demonstrating a clinical sensitivity of 50% at 99% specificity in detecting ovarian cancer cases with an area under the receiver operator curve of 0.90. We then establish a logistic regression model that could be used to identify high-risk patients for subsequent clinical follow-up and monitoring. The results of this study support the utility of PapDREAM as a simple, low-cost screening method with the potential to integrate with existing clinical workflows for early detection of ovarian cancer. KEY POINTS: We present a microfluidic platform for detection and analysis of rare, heterogeneously methylated DNA within Pap specimens towards detection of ovarian cancer. The platform achieves high sensitivity (fractions <0.00005%) at a suitably low cost (∼$25) for routine screening applications. Furthermore, it provides molecule-by-molecule quantitative analysis to facilitate further study on the effect of heterogeneous methylation on cancer development.

Morphologic and Molecular Heterogeneity of High-grade Serous Carcinoma Precursor Lesions.

Serous tubal intraepithelial carcinoma (STIC) is the fallopian tube precursor lesion for most cases of pelvic high-grade serous carcinoma (HGSC). To date, the morphologic, molecular, and clinical heterogeneity of STIC and a less atypical putative precursor lesion, termed serous tubal intraepithelial lesion, has not been well characterized. Better understanding of precursor heterogeneity could impact the clinical management of women with incidental STICs (without concurrent carcinoma) identified in cases of prophylactic or opportunistic salpingectomy. This study analyzed morphologic and molecular features of 171 STICs and 21 serous tubal intraepithelial lesions. We assessed their histologic features, Ki-67 and p53 staining patterns, and genome-wide DNA copy number alterations. We classified all precursor lesions into 2 morphologic subtypes, one with a flat surface (Flat) and the other characterized by budding, loosely adherent, or detached (BLAD) morphology. On the basis of pathology review by a panel of 8 gynecologic pathologists, we found 87 BLAD, 96 Flat, and 9 indeterminate lesions. As compared with Flat lesions, BLAD lesions were more frequently diagnostic of STIC ( P <0.0001) and were found concurrently with HGSC ( P <0.0001). BLAD morphology was also characterized by higher Ki-67 proliferation index ( P <0.0001), presence of epithelial stratification ( P <0.0001), and increased lymphocyte density ( P <0.0001). BLAD lesions also exhibited more frequent DNA copy number gain/amplification at the CCNE1 or CMYC loci canonical to HGSCs ( P <0.0001). Both BLAD morphology and STIC diagnoses are independent risk factors for an elevated Ki-67 proliferation index. No correlation was observed between BLAD and Flat lesions with respect to patient age, presence of germline BRCA1/2 mutation, or p53 staining pattern. These findings suggest that tubal precursor lesions are morphologically and molecularly heterogeneous, laying the foundation for further studies on the pathogenesis of HGSC initiation and identifying histologic features predictive of poor patient outcomes.

Machine learning to detect the SINEs of cancer.

We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a machine learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to 7615 samples from 5178 individuals, 2073 with solid cancer and the remainder without cancer. Samples from patients with cancer and controls were prespecified into four cohorts used for model training, analyte integration, and threshold determination, validation, and reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the validation cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and eight common protein biomarkers detected 51% of the cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature-the global reduction of AluS subfamily elements in the circulating DNA of patients with solid cancer. We confirmed this reduction through the analysis of another independent dataset obtained with a different approach (whole-genome sequencing). The evaluation of Alu elements may therefore have the potential to enhance the performance of several methods designed for the earlier detection of cancer.