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Adult-type granulosa cell tumors (aGCT) are rare ovarian sex cord tumors with few effective treatments for recurrent disease. The objective of this study was to characterize the tumor microenvironment (TME) of primary and recurrent aGCTs and to identify correlates of disease recurrence. Total RNA sequencing (RNA-seq) was performed on 24 pathologically confirmed, cryopreserved aGCT samples, including 8 primary and 16 recurrent tumors. After read alignment and quality-control filtering, DESeq2 was used to identify differentially expressed genes (DEG) between primary and recurrent tumors. Functional enrichment pathway analysis and gene set enrichment analysis was performed using “clusterProfiler” and “GSVA” R packages. TME composition was investigated through the analysis and integration of multiple published RNA-seq deconvolution algorithms. TME analysis results were externally validated using data from independent previously published RNA-seq datasets. A total of 31 DEGs were identified between primary and recurrent aGCTs. These included genes with known function in hormone signaling such as LHCGR and INSL3 (more abundant in primary tumors) and CYP19A1 (more abundant in recurrent tumors). Gene set enrichment analysis revealed that primarily immune-related and hormone-regulated gene sets expression was increased in recurrent tumors. Integrative TME analysis demonstrated statistically significant depletion of cancer-associated fibroblasts in recurrent tumors. This finding was confirmed in multiple independent datasets. Implications: Recurrent aGCTs exhibit alterations in hormone pathway gene expression as well as decreased infiltration of cancer-associated fibroblasts, suggesting dual roles for hormonal signaling and TME remodeling underpinning disease relapse.

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Adult-type granulosa cell tumors (aGCT) are rare ovarian sex cord tumors with few effective treatments for recurrent disease. The objective of this study was to characterize the tumor microenvironment (TME) of primary and recurrent aGCTs and to identify correlates of disease recurrence. Total RNA sequencing (RNA-seq) was performed on 24 pathologically confirmed, cryopreserved aGCT samples, including 8 primary and 16 recurrent tumors. After read alignment and quality-control filtering, DESeq2 was used to identify differentially expressed genes (DEG) between primary and recurrent tumors. Functional enrichment pathway analysis and gene set enrichment analysis was performed using “clusterProfiler” and “GSVA” R packages. TME composition was investigated through the analysis and integration of multiple published RNA-seq deconvolution algorithms. TME analysis results were externally validated using data from independent previously published RNA-seq datasets. A total of 31 DEGs were identified between primary and recurrent aGCTs. These included genes with known function in hormone signaling such as LHCGR and INSL3 (more abundant in primary tumors) and CYP19A1 (more abundant in recurrent tumors). Gene set enrichment analysis revealed that primarily immune-related and hormone-regulated gene sets expression was increased in recurrent tumors. Integrative TME analysis demonstrated statistically significant depletion of cancer-associated fibroblasts in recurrent tumors. This finding was confirmed in multiple independent datasets.Implications:Recurrent aGCTs exhibit alterations in hormone pathway gene expression as well as decreased infiltration of cancer-associated fibroblasts, suggesting dual roles for hormonal signaling and TME remodeling underpinning disease relapse.

S1. Heatmap of unsupervised hierarchical clustering of the top 1000 most variable genes.S2. Violin plots showing the expression levels of genes previously identified as differentially expressed genes between primary and recurrent tumors in Haltia et al., 2020.S3. Gene set enrichment analysis performed with GO terms and KEGG pathways showing that primarily immune-related and hormone-regulated gene sets expression are altered between primary and recurrent aGCTs.S4. Gene set enrichment analysis results showing that top enriched gene sets are significantly enriched in recurrent tumors in comparison with primary tumors.S5. Boxplot showing the fraction of each noncancerous cell type identified by CIBERSORTx (A) and xCell (B) in primary and recurrent tumor samples.S6. Heatmap showing the correlation between immune cells fractions.

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PDF file - 58K, Immunohistochemical analysis of pS6rp expression in endometrial cancer xenograft tumors.

PDF file - 50K, Western blot showing PTEN and OCT1 expression.

Metformin is an oral biguanide commonly used for the treatment of type II diabetes and has recently been demonstrated to possess antiproliferative properties that can be exploited for the prevention and treatment of a variety of cancers. The mechanisms underlying this effect have not been fully elucidated. Using both in vitro and in vivo models, we examined the effects of metformin on endometrial tumors with defined aberrations in the PI3K/PTEN/mTOR and MAPK signaling pathways to understand metformin mechanism of action and identify clinically useful predictors of response to this agent. In vitro assays of proliferation, cytotoxicity, and apoptosis were used to quantify the effects of metformin on endometrial cancer cell lines with mutations in the PI3K/PTEN/mTOR and MAPK signaling pathways. The in vivo effects of oral metformin on tumor progression were further examined using xenograft mouse models of endometrial cancer. K-Ras localization was analyzed by confocal microscopy using GFP-labeled oncogenic K-Ras and by immunoblot following subcellular fractionation. Metformin inhibited cell proliferation, induced apoptosis, and decreased tumor growth in preclinical endometrial cancer models, with the greatest response observed in cells harboring activating mutations in K-Ras. Furthermore, metformin displaces constitutively active K-Ras from the cell membrane, causing uncoupling of the MAPK signaling pathway. These studies provide a rationale for clinical trials using metformin in combination with PI3K-targeted agents for tumors harboring activating K-Ras mutations, and reveal a novel mechanism of action for metformin. Mol Cancer Ther; 12(12); 2847–56. ©2013 AACR.

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Animation of PCA for Figure 1

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

Supplementary Table from A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

Purpose:To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.Experimental Design:Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed.Results:A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76–0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84–0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84–0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone.Conclusions:A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

Supplementary Data from A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

Supplementary Figure from A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses

Purpose: To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts. Experimental Design: Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM. The performance of the metabolite panel was evaluated in an independent set of sera from 118 ovarian cancer cases and 56 subjects with BPM. The contributions of the panel for improving upon the performance of ROMA were further assessed. Results: A 7-marker metabolite panel (7MetP) developed in the training set yielded an AUC of 0.86 [95% confidence interval (CI): 0.76–0.95] for early-stage ovarian cancer in the independent test set. The 7MetP+ROMA model had an AUC of 0.93 (95% CI: 0.84–0.98) for early-stage ovarian cancer in the test set, which was improved compared with ROMA alone [0.91 (95% CI: 0.84–0.98); likelihood ratio test P: 0.03]. In the entire specimen set, the combined 7MetP+ROMA model yielded a higher positive predictive value (0.68 vs. 0.52; one-sided P < 0.001) with improved specificity (0.89 vs. 0.78; one-sided P < 0.001) for early-stage ovarian cancer compared with ROMA alone. Conclusions: A blood-based metabolite panel was developed that demonstrates independent predictive ability and complements ROMA for distinguishing early-stage ovarian cancer from benign disease to better inform clinical decision making.

ImportanceDespite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics.ObjectiveTo develop and characterize a gross morphologic classification system for HGSOC.Design, Setting, and ParticipantsThis cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021.ExposuresGross tumor morphologic characteristics.Main Outcomes and MeasuresClinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared.ResultsOf 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10−24), hypoxia (FDR q-value, 1.52 × 10−5), and angiogenesis pathways (FDR q-value, 2.11 × 10−2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10−9) and cell cycle progression (FDR q-value, 1.10 × 10−5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes.Conclusions and RelevanceThis study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.

Background: Adult-type granulosa cell tumors (AGCT) are rare ovarian sex cord tumors that exhibit near-universal FOXL2 c.C402G (p.Cys134Trp) hotspot mutations. AGCT recurrence is difficult to predict and is almost always incurable after relapse. Little is known about the relationship between intra-tumor immune and stromal composition and AGCT relapse. Objective: To compare global gene expression profiles between primary and recurrent AGCTs, characterize the tumor microenvironment (TME), and identify correlates of disease recurrence. Methods: Total RNA sequencing was performed on 24 pathologically confirmed, cryopreserved AGCT samples, including 8 primary and 16 recurrent tumors. Standard methods were applied for read alignment, quality control, and quantification of gene-specific read counts. DESeq2 was used to identify statistically significant (adjusted P-value < 0.05) differentially expressed genes between primary and recurrent tumors with fold change > 2. Gene set enrichment analysis was performed using clusterProfiler. Integrative TME composition de-convolution was performed using multiple published algorithms including CIBERSORTx, quanTIseq, xCell, MCP-counter, and EPIC. TME analysis results were externally validated using data from smaller, previously published RNA sequencing datasets. Results: Thirty-one genes were identified as differentially expressed between primary and recurrent AGCTs, including NELL2, GDF6, TUBB2B, AQP3. These included genes with known function in hormone signaling such as LHCGR (adjusted P-value = 0.002) and INSL3 (adjusted P-value = 0.017) which were highly expressed in primary tumors and CYP19A1 (adjusted P-value = 0.009) which was highly expressed in recurrent tumors. Gene set enrichment analysis revealed increased expression of hormone-regulated and immune-related gene sets in recurrent tumors. Integrative, multi-platform TME analysis showed recurrent AGCT to exhibit reduced fractions of cancer-associated fibroblasts and enrichment of myeloid lineages such as neutrophils and macrophages. Conclusions: Recurrent AGCTs exhibit alterations in hormone pathway gene expression as well as decreased infiltration of cancer-associated fibroblasts, suggesting dual roles for hormonal signaling and TME remodeling underpinning disease relapse. Citation Format: Eleonora Khlebus, Veena K. Vuttaradhi, Thomas Welte, Namrata Khurana, Joseph Celestino, Hannah C. Beird, Curtis Gumbs, Latasha Little, Alejandra Flores Legarreta, Tri Nguyen, Barrett Lawson, Russell R. Broaddus, David M. Gershenson, P. Andrew Futreal, R. Tyler Hillman. Tumor microenvironment composition correlates with relapse in ovarian granulosa cell tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2503.

Background: Clonal hematopoiesis (CH) is identified as the presence of clonal populations of hematopoietic stem cells (HSC). Hematopoietic lineage differentiation is subjected to genetic mutations that, due to fitness advantages, might give rise to clonally expanded populations. Clonal hematopoiesis of indeterminate potential (CHIP) is defined as the outgrowth of a single clone driven by acquired somatic mutation(s) in HSCs, in the absence of hematological abnormalities. Previous studies have been shown the association of CH with aging and a higher risk of developing secondary hematologic malignancies in cancer patients treated with chemotherapy agents. It is therefore of great interest to study CH incidence prior to and post chemotherapy exposure and its association with the evolution of hematologic malignancies. We aimed to characterize CHIP variants of a highly selected group of patients with high-grade serous ovarian cancer (HGSC) who underwent neoadjuvant chemotherapy; moreover, while previous CHIP studies are largely knowledge based and are limited to known hematologic genes or target gene panels, our study discovers novel CHIP mutations. Methods: Comprehensive ultra-high-depth whole exome sequencing using unique molecular barcode technologies was performed using plasma-derived cell-free DNA and matched white blood cells DNA and tumor DNA from pre-NACT (n=12) and post-NACT (n=12) samples of patients with HGSC who have excellent or poor response to NACT. Using spike-in mutated DNAs as positive controls, we detected variant alleles at 1% variant allele frequency. Results: We identified on average about 3,000 candidate CHIP variants in one patient. Among these, 1,977 variants affecting 1,375 genes were recurrently found in more than one patient. These CHIP genes include not only previous reported CHIP genes (e.g. DNMT3A, JAK2, TET2, and KMT2D) but also many novel CHIP candidates (such as RPTN, MTCH2, FAM186A, CACNA1A, FCGBP, and MUC3A). A number of CHIP mutations were uniquely found enriched in post-chemotherapy samples (e.g. ARID1A T290P, TP53 G245D, SMARCA4 G495D, and CIC T2456P). Interestingly, there is a strong enrichment of COSMIC cancer census genes in CHIP genes identified in every patient. Conclusions: Our findings corroborate the notion that CHIP mutations are present in nonmalignant blood cells of patients with HGSC, and some are enriched after chemotherapy. Moreover, our innovative sequencing approach allowed discovery of novel candidate CHIP genes. The systematic identification of CHIP in patients with HGSC might be an important new clinical consideration when establishing chemotherapy protocols. Citation Format: Sara Corvigno, Jun Yao, Li Zhao, Amma Asare, Joseph Celestino, Richard Hajek, Ency Arboleda Goette, Elaine Stur, Emine Bayraktar, Mark S Kim, Ping Song, Qingxiu Zhang, Xingzhi Song, Mohammad Mohammad, Kenna Shaw, Jianhua Zhang, Karen Lu, Amir Jazaeri, Shannon Westin, Sanghoon Lee, Anil Sood. Genomic profiling of chemotherapy-related clonal hematopoiesis in patients with high-grade serous ovarian cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5473.

BACKGROUND Early detection of ovarian cancer could significantly improve patient outcomes. Cancer antigen 125 (CA 125) is elevated in sera from approximately 60% of patients with early-stage (I/II) disease. Sensitivity might be improved through the combination of CA 125 with other biomarkers. Among potential biomarkers, antigen-autoantibody (Ag-AAb) complexes have received relatively little attention. METHODS Luminex-based immunoassays were used to measure human epididymis protein 4 (HE4), anti-HE4 autoantibody, and HE4 Ag-AAb complexes in sera from patients with early- (n = 73) and late-stage ovarian cancers (n = 49) at the time of diagnosis and from asymptomatic women with (n = 15) or without ovarian cancer (n = 212) enrolled in the Normal Risk Ovarian Cancer Screening Study. RESULTS At 98% specificity for healthy, asymptomatic women, 7% of patients with early-stage (I/II) ovarian cancer and 4% of patients with late-stage (III/IV) disease had elevated levels of HE4 autoantibody, whereas elevated levels of HE4 Ag-AAb complexes were detected in sera from 38% of early-stage cases and 31% of late-stage cases. Complementarity was observed in receiver operating characteristic (ROC) curves between HE4 Ag-AAb complexes and CA 125 levels in early-stage ovarian cancer (P

Non-surgical treatment options for low-grade endometrial cancer and precancerous lesions are a critical unmet need for women who wish to preserve fertility or are unable to undergo hysterectomy. The PI3K/AKT/mTOR pathway is frequently activated in endometrial cancers and has been associated with resistance to endocrine therapy, making it a compelling target for early stage disease. Oral everolimus, an inhibitor against mTORC1, has shown clinical benefit in advanced or recurrent disease but has severe adverse effects that may lead to treatment interruption or dose reduction. To overcome this, we developed a polymer-based intrauterine delivery system to achieve persistent, local delivery of everolimus without systemic exposure. In vivo studies, using a rat model, showed that a poly(propylene fumarate)-based rod loaded with everolimus achieved everolimus delivery to the endometrium with levels similar to oral administration, but with limited systemic exposure and up to 84 days of release. Biological activity of everolimus delivered with this system was confirmed, measured by reduced lumen epithelial cell height and PI3K pathway biomarkers. This study shows a promising new delivery approach for anti-cancer drugs for non-surgical treatment of low-grade endometrial cancer.

BACKGROUND: Immunotherapy has become a powerful treatment option for several solid tumor types. The presence of tumor-infiltrating lymphocytes (TIL) is correlated with better prognosis in ovarian cancer, pointing at the possibility to benefit from harnessing their anti-tumor activity. This preclinical study explores the feasibility of adoptive cell therapy (ACT) with TIL using an improved culture method. METHODS: TIL from high-grade serous ovarian cancer were cultured using a combination of IL-2 with agonistic antibodies targeting 4-1BB and CD3. The cells were phenotyped using flow cytometry in the fresh tissue and after expansion. Tumor reactivity was assessed against HLA-matched ovarian cancer cell lines via IFN-γ ELISPOT. RESULTS: Ovarian cancer is highly infiltrated with CD8(+) TIL that are preferentially and robustly expanded with the addition of the agonistic antibodies. With a 95% success rate, the TIL are grown to ≥ 100 × 10(6) cells in 2–3 weeks without over differentiation. In addition, the CD8(+) TIL grown with this method showed HLA-restricted tumor recognition. CONCLUSIONS: These results indicate the viability of TIL ACT for refractory ovarian cancer by allowing for the large expansion of anti-tumor TIL in a short time and consistent manner.

Background: Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (CGR) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Through comprehensive omics analyses, we previously characterized molecular and cellular profiles of highly clinically defined HGSC from patients who had CGR versus those triaged to NACT. However, clinically useful predictive biomarkers for such distinctions are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. Here, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC. Methods: Serum-derived medium/large size EVs from patients with HGSC treated under a systematic surgical algorithm were isolated following standard methods of the International Society for Extracellular Vesicles. Patients had either complete gross resection after primary surgery (R0, n=3); poor response to NACT (NACT-PR, n=4), or excellent response to NACT with carboplatin and paclitaxel (NACT-ER, n=3); tissue and matched germline blood samples have already been comprehensively analyzed (Lee et al, Cell Reports, 2020). The isolated EV-DNA and EV-RNA were subjected to whole-genome sequencing and RNA sequencing, respectively. Results: We identified somatic EV-DNA alterations in cancer hallmark genes, including FAT1 and KMT2D as the most frequent mutated genes. Interestingly, we found alterations in ovarian cancer-related genes, including BRCA2 and RAD51 in R0; BRCA2 in NACT-ER; TP53, CDK13, CDK12, BRAF, AKT2, and ARID1A in NACT-PR patients. We also identified 26,338 genes expressed in the EV-RNA transcriptomic profiles. The analysis of the enrichment of cancer hallmark pathways showed that the R0 group was more enriched in the interferon α/γ, PI3K/AKT/mTOR signaling, and DNA repair pathways. Interestingly, we also identified 6,757 differentially expressed genes (DEGs) in the CGR versus the NACT groups (absolute log2-fold change ≥2 and adjusted p-value Conclusions: Taken together, our preliminary data suggest that molecular characteristics of EVs could provide an accurate prediction of patients with HGSC who can undergo CGR with surgery and respond to chemotherapy. Citation Format: Li Zhao, Shaolin Ma, Nicole D. Fleming, Joseph Celestino, Mark S. Kim, Richard A. Hajek, Nicholas B. Jennings, Erika J. Thompson, Hongli Tang, Shannon N. Westin, Amir A. Jazaeri, Jianhua Zhang, P Andrew Futreal, Anil K. Sood, Sanghoon Lee. Distinct molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5106.

Background: High-grade serous ovarian cancer (HGSC) is the most aggressive epithelial ovarian cancer, exhibiting tumor heterogeneity, molecular abnormality, and variable clinical outcomes. The heterogeneity and apparent adaptability of the HGSC genome under selective pressure by chemotherapy likely explain the high rates of drug resistance in HGSC. However, the underlying mechanisms of drug resistance are not well understood. Following our previous findings of significant distinct molecular and cellular characteristics in pre-treatment tumor samples from highly clinically annotated HGSC patients who received neoadjuvant chemotherapy (NACT), we examined post-treatment transcriptomic changes associated with excellent or poor responders to NACT in HGSC patients. Methods: Thirty tumor tissues (pre- and post-treatment) after 3 to 4 cycles of NACT were collected from HGSC patients at interval cytoreductive debulking surgery from the following groups: excellent response to NACT with carboplatin/paclitaxel (post-ER, n=8); poor response to NACT (post-PR, n=8). Primary or metastatic sites for each patient were obtained (n=13, post-ER; n=17, post-PR) and subjected to RNA sequencing. The downstream bioinformatics analysis was then performed and compared with the data from the matched pre-NACT samples from the same patients (Lee et al., Cell Reports, 2020). Results: We identified a total of 9,764 upregulated and 2,762 downregulated differentially expressed genes (DEGs, absolute log2FC >=2, adj-p Conclusions: Our transcriptomic analysis revealed distinct transcripts changes in post-NACT vs pre-NACT tumor tissues from HGSC patients with excellent or poor response to the NACT. These findings could enhance treatment decision-making and rationale for developing alternative therapies for patients with HGSC. Citation Format: Sanghoon Lee, Li Zhao, Nicole D. Fleming, Joseph Celestino, Richard A. Hajek, Margaret B. Morgan, Yan Liu, Shannon N. Westin, Amir A. Jazaeri, Jinsong Liu, Jianhua Zhang, P Andrew Futreal, Anil K. Sood. Transcriptomic profiles of response to neoadjuvant chemotherapy in patients with high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5738.

MYC is an oncogenic driver in the pathogenesis of ovarian cancer. We previously demonstrated that MYC regulates polyamine metabolism in triple-negative breast cancer (TNBC) and that a plasma polyamine signature is associated with TNBC development and progression. We hypothesized that a similar plasma polyamine signature may associate with ovarian cancer (OvCa) development. Using mass spectrometry, four polyamines were quantified in plasma from 116 OvCa cases and 143 controls (71 healthy controls + 72 subjects with benign pelvic masses) (Test Set). Findings were validated in an independent plasma set from 61 early-stage OvCa cases and 71 healthy controls (Validation Set). Complementarity of polyamines with CA125 was also evaluated. Receiver operating characteristic area under the curve (AUC) of individual polyamines for distinguishing cases from healthy controls ranged from 0.74–0.88. A polyamine signature consisting of diacetylspermine + N-(3-acetamidopropyl)pyrrolidin-2-one in combination with CA125 developed in the Test Set yielded improvement in sensitivity at &gt, 99% specificity relative to CA125 alone (73.7% vs 62.2%, McNemar exact test 2-sided P: 0.019) in the validation set and captured 30.4% of cases that were missed with CA125 alone. Our findings reveal a MYC-driven plasma polyamine signature associated with OvCa that complemented CA125 in detecting early-stage ovarian cancer.

Objectives: Despite similar histologic appearance amongst high-grade serous ovarian cancers (HGSOC), anecdotally there are differences in gross appearance. However, no systematic framework to classify morphologic differences exists. Therefore, we aimed to determine whether high-grade serous ovarian cancers (HGSOC) can be reliably divided into distinct gross morphologic subtypes and to assess clinical outcomes and molecular features of these subtypes. Methods: A retrospective review was performed of video-recordings from patients who underwent laparoscopic assessment of disease burden prior to primary debulking surgery (PDS) or neoadjuvant chemotherapy (NACT). Video recordings were reviewed by at least 2 physicians. A total of 4 sites (diaphragm, omentum, peritoneum, and pelvis) were assessed and classified as type I (deep, infiltrative disease with distortion of surrounding tissue) or type II (superficial, exophytic disease bordered by normal tissue). Tumor tissues from 16 of these chemotherapy-naive patients were analyzed by multi-platform omics (RNA sequencing, proteomics). Clinical outcomes were assessed utilizing a prospectively collected database and compared by morphology using t-test or Fisher's exact test. Results: Of the 99 evaluable patients, 60 exhibited uniform morphology at all involved metastatic sites (65% type I and 35% type II), and 81 exhibited a predominating morphology (58% type I and 42% type II). A total of 164 images were reviewed by a third physician with 83.5% inter-rater concordance (κ=0.6446). Patients with uniform type 1 (n=34)tumor morphology were more likely to exhibit an excellent response to NACT (defined as radiologic or CA-125 complete response) than those with type II (n=16) tumor morphology (47% vs 18%, p=0.13). Patients with type II predominant tumor morphology had a significantly higher estimated blood loss at the time of interval debulking surgery (p=0.008) as well as longer operative time (p=0.03) compared with type I tumor morphology. Patients with complete type II morphology were more likely to have a modified Fagotti score of Conclusions: There are at least two distinct gross morphological patterns of HGSOC with unique molecular differences and responses to chemotherapy. These findings could have major clinical implications for tailored therapeutic strategies. Download : Download high-res image (97KB) Download : Download full-size image

Adult-type granulosa cell tumors of the ovary (aGCTs) are rare gynecologic malignancies that exhibit a high frequency of somatic FOXL2 c.C402G (p.Cys134Trp) mutation. Treatment of relapsed aGCT remains a significant clinical challenge. Here we show, using whole-exome and cancer gene panel sequencing of 79 aGCTs from two independent cohorts, that truncating mutation of the histone lysine methyltransferase gene KMT2D (also known as MLL2) is a recurrent somatic event in aGCT. Mono-allelic KMT2D-truncating mutations are more frequent in recurrent (10/44, 23%) compared with primary (1/35, 3%) aGCTs (p = 0.02, two-sided Fisher’s exact test). IHC detects additional non-KMT2D-mutated aGCTs with loss of nuclear KMT2D expression, suggesting that non-genetic KMT2D inactivation may occur in this tumor type. These findings identify KMT2D inactivation as a novel driver event in aGCTs and suggest that mutation of this gene may increase the risk of disease recurrence., Adult-type granulosa cell tumors of the ovary (aGCTs) are rare and recurrence is difficult to treat. Here, the authors observe in aGCT a novel recurrent somatic truncating mutation of KMT2D, more frequent in recurrent aGCT, and also non-genetic loss of KMT2D expression.

Background: While high-grade serous ovarian cancers (HGSC) look alike at a histological level, there is marked variation in clinical outcomes; however, the underlying mechanisms are not well understood. We previously highlighted significant distinct molecular and cellular characteristics in highly clinically annotated HGSC tumor samples from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT). Neurofibromatosis type 1 (NF1) is known to negatively regulate the Ras/MAPK signaling pathways and tumorigenesis. Here, we specifically validate the higher loss of NF1 copy number exhibited in the R0 compared to the NACT groups in patients with HGSC. Methods: Fresh-frozen tumor biopsies were collected from patients with HGSC treated under a systematic surgical algorithm: complete gross resection after primary surgery (R0, n=40); poor tumor response to NACT (NACT-PR, n=26); excellent tumor response to NACT with carboplatin and paclitaxel (NACT-ER, n=14). Primary or metastatic tumor sites for each patient were obtained pre-treatment and subjected to high-depth targeted DNA sequencing. Results: The average coverage of 568X for tumors and 291X for germline controls (matched blood samples) was obtained by targeted sequencing for each sample from the entire cohort. The median numbers of non-synonymous somatic mutations identified in the panel sequencing were 5 in R0, 3 in NACT-ER, and 5 in NACT-PR. Sixty-nine of the 80 samples (86.25%) had alterations in at least one of the ovarian cancer-related genes. The most frequently altered genes including somatic mutations and copy number variations were TP53 (68%), NF1 (65%) and ERBB2 (62%) in the R0 group whereas TP53 (50%), AKT1 (48%) and TERT (42%) in the NACT group. Gene alteration enrichment was evaluated by comparing between two groups. 17 genes were found to be enriched for alterations in the R0 group comparing to the NACT group; MLH3 (OR= 15.03, p Conclusions: Our findings, using an independent validation cohort of patients, verified the higher loss of NF1 copy number in the R0 versus the NACT group. These findings could have major implications for clinical decision making and developing novel therapies for patients with HGSC. Citation Format: Sanghoon Lee, Li Zhao, Joseph Celestino, Richard A. Hajek, Margaret B. Morgan, Mark S. Kim, Shannon N. Westin, Amir A. Jazaeri, Nicole D. Fleming, Jinsong Liu, Jianhua Zhang, P Andrew Futreal, Anil K. Sood. NF1 copy number alterations in clinically-defined subsets of high-grade serous ovarian cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2200.

Understanding tumor microenvironment is critical to improving conservative management (non-surgical) strategies for early stage, low grade endometrial cancer (EC). This remains an unmet clinical need for women who wish to maintain fertility and those who cannot undergo surgery due to medical co-morbidities. Current regimens rely on progestin treatment, but resistance and early relapse require improved therapeutic strategies. We sought to evaluate alterations in gene expression in the epithelial and stromal compartment of EC compared to normal endometrium to identify targets for combination therapies. RNA was extracted from microdissected epithelial and stromal compartments of formalin fixed paraffin embedded early stage, low grade EC and normal endometrium (NE). Comprehensive transcriptome profiling was performed with Affymetrix Clariom D assay and pathway analysis was performed. Immunohistochemistry (IHC) was used for validation. Functional studies of differentially expressed genes were performed in Hec1A EC cell lines. Among differentially expressed genes in EC vs NE, multiple altered signaling pathways were identified. EIF2 signaling, eIF4 and p70S6K signaling, and PI3K/AKT/mTOR were the most significant pathways activated in both epithelial and stromal compartments. In the epithelia compartment, the most significant gene expression changes included reduced expression of RBPMS (RNA Binding Protein with Multiple Splicing), SORD (Sorbitol Dehydrogenase), DDX17 (DEAD-Box Helicase 17), and TPT1 (Translationally-Controlled Tumor Protein) in EC, while MTDH (Metadherin) was significantly increased in EC. Similar changes were observed in the stroma compartment, but with lower fold changes than that observed in gland. Together with decreased RBPMS expression, decreased RBPMS-interacting molecules IGF2, TCF7L2 (Transcription Factor 7 Like 2), FOS (Proto-Oncogene C-Fos) and increased GPS2 (G protein Pathway Suppressor 2) were also observed. Differential expression of proteins in gland and stroma was also confirmed by IHC. An inverse correlation of RBPMS expression and EC proliferation was also observed in EC at the protein level. Enhanced AKT and S6 protein phosphorylation were observed by RBPMS silencing in Hec1A endometrial cells. Reverse Phase Protein Array demonstrated activation of Caveolin 1, FOXO3 (Forkhead Box O3), MT-CO1 (Mitochondrially Encoded Cytochrome C Oxidase I), L1CAM (L1 Cell Adhesion Molecule) with RBPMS silencing in Hec1A cell. These molecules are involved in pathways such as molecular mechanisms of cancer, estrogen receptor signaling, and senescence pathway. While estrogen-regulated changes were prominent in early stage low-grade EC, the identification of additional signaling changes provide support for an ongoing trial of levonorgestrel IUD + everolimus (mTOR inhibitor) and can be probed further to identify new targets for combination conservative management strategies. Additionally, biomarkers from these pathways, such as RBPMS, can be studied to guide the selection of progestin-only therapy versus combination therapy. Citation Format: Qian Zhang, Xiaoping Su, Joseph Celestino, Ying Yuan, Samuel C. Mok, Karen H. Lu, Melinda S. Yates. Compartment-specific profiling for evaluation of disrupted signaling in early stage, low-grade endometrial cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference: Endometrial Cancer: New Biology Driving Research and Treatment; 2020 Nov 9-10. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(3_Suppl):Abstract nr PO049.

Background: High-grade serous ovarian cancer (HGSOC) remains the leading cause of death from gynecologic malignancies. Here, we examined tumoral proteome changes following neoadjuvant chemotherapy (NACT) to identify potential predictive and prognostic biomarkers of response to primary chemotherapy. Methods: A total of 65 tissue specimens from 10 patients with advanced-stage HGSOC were collected from matched pre- and post-NACT (3 cycles of dose-dense paclitaxel and carboplatin). Protein expression was assessed using reverse-phase protein arrays (RPPA). All relative protein levels using 297 antibodies were normalized by the expression level of pre-treatment samples, and then protein expression alterations and functional analyses were performed by Reactome pathway analysis followed by statistical analysis. Results: The protein expression patterns of samples tended to cluster according to the time point (pre- and post-treatment) by a non-supervised clustering analysis using all the proteins assessed in the RPPA panel. Five differentially expressed proteins among 239 proteins (adj. p Conclusion: Our findings identified significant proteomic alterations following NACT, and could provide insights into interval proteomic alterations following induction chemotherapy in advanced-stage ovarian cancer patients. These data present information to optimize future clinical trial designs for patients with ovarian cancer. Citation Format: Sanghoon Lee, Li Zhao, Joseph Celestino, Kelly M. Rangel, Richard A. Hajek, Mark S. Kim, Sara E. Sharafi, Jinsong Liu, Nicole D. Fleming, Karen H. Lu, Jianhua Zhang, P. Andrew Futreal, Gordon B. Mills, Shannon N. Westin, Anil K. Sood, Amir A. Jazaeri, Robert L. Coleman. Functional proteomic aberrations post-chemotherapy with paclitaxel and carboplatin in patients with advanced ovarian cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2941.

Understanding tumor microenvironment is critical to improving conservative management (non-surgical) strategies for early stage, low grade endometrial cancer (EC). This remains an unmet clinical need for women who wish to maintain fertility and those who cannot undergo surgery due to medical co-morbidities. Current regimens rely on progestin treatment, but resistance and early relapse require improved therapeutic strategies. We sought to evaluate alterations in gene expression in the epithelial and stromal compartment of EC compared to normal endometrium to identify targets for combination therapies. RNA was extracted from microdissected epithelial and stromal compartments of formalin fixed paraffin embedded early stage, low grade EC and normal endometrium (NE). Comprehensive transcriptome profiling was performed with Affymetrix Clariom D assay and pathway analysis was performed. Immunohistochemistry (IHC) was used for validation. Functional studies of differentially expressed genes were performed in EC cell lines, ECC-1 and Hec1A. Focusing on differentially expressed genes in the epithelial compartment of EC vs NE, multiple activated signaling pathways were identified, including eIF2 signaling, eIF4 and p70S6K signaling, PI3K/AKT/mTOR, and hormone signaling. Top gene expression changes with significantly lower expression in EC included RBPMS (RNA-binding protein with multiple splicing), SORD (sorbitol dehydrogenase), DDX17 (DEAD-box helicase 17), and TPT1 (translationally-controlled tumor protein) gene expression, while MTDH (metadherin) was significantly increased in EC. Differential expression of proteins coded by these genes was confirmed by IHC. Additionally, RBPMS silencing enhanced AKT and S6 protein phosphorylation in Hec1A cells and forced expression of RBPMS in ECC-1 cells attenuated Erk1/2 MAP kinase activation. Expression of RBPMS inhibited cell proliferation and knockdown of RBPMS increased proliferation. Treatment of EC cells with everolimus (mTOR inhibitor) resulted in differential inhibition of proliferation based on RBPMS expression. Communication between tumor and stroma is also being evaluated. While estrogen-regulated changes were prominent in early stage low-grade EC, the discovery of alterations in other signaling pathways suggest additional targets for conservative management of the disease. The identification of signaling nodes shared between hormone-regulated pathways and mTOR signaling provides further justification for the ongoing combination therapy trial (progestin plus everolimus). Additionally, biomarkers from these pathways, such as RBPMS, can be studied to guide the selection of progestin-only therapy versus combination therapy. Citation Format: Qian Zhang, Xiaoping Su, Joseph Celestino, Ying Yuan, Samuel C. Mok, Karen H. Lu, Melinda S. Yates. Identification of molecular targets for conservative management of early stage, low-grade endometrial cancer through compartment-specific transcriptome profiling [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4143.

The two bes- known ovarian cancer biomarkers, CA125 and HE4, are neither adequately sensitive nor specific to be used to screen the general population for early stages of ovarian cancer. The purpose of this study was to develop a multiprotein classifier that would combine additional protein biomarkers with CA125 and HE4 in order to increase their sensitivity and specificity. We used the Olink Proseek Multiplex Oncology II panel to simultaneously quantify the expression levels of 92 cancer-related proteins using proximity extension assay technology. We analyzed serum from two institutions: 143 women with early-stage (I/II) ovarian cancer (serous, endometrioid, clear-cell, mucinous, and others) and compared the values obtained to 341 age-matched healthy women. We identified 24 proteins whose relative expression between cancers and controls was significantly different between the samples from the two institutions; therefore, we removed these proteins from downstream analysis. Principle Component Analysis and T-distributed Stochastic Neighbor Embedding separated the ovarian cancer samples from the healthy controls, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with previously measured clinical values for CA125 (correlation coefficient of 0.81). CA125 and HE4 were detected at low levels in samples from healthy women, while higher levels were observed in the early-stage ovarian cancer cases. We identified 31 proteins that differed significantly (p < 0.001) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 11 proteins had an estimated area under the ROC curve of 0.70 or greater. CA125 alone achieved a sensitivity of 81.0% at a specificity of 98%. However, by adding three proteins to CA125, we increased the assay sensitivity to 86.2%, while holding the specificity fixed at 98%. In conclusion, our data demonstrate that the inclusion of several protein biomarkers can improve the sensitivity and specificity of CA125 alone for the detection of early stages of ovarian cancer. Validation of this multiprotein classifier is currently under way using serum samples from other institutions. Citation Format: Amy P. Skubitz, Kristin L. Boylan, Timothy K. Starr, Xuan Pu, Qing Cao, Kate Geschwind, Robert C. Bast, Jr., Karen H. Lu, Joseph Celestino, Ashley J. Petersen. A serum protein biomarker signature for the detection of early stages of ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B43.

SUMMARY The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC), which is the most lethal gynecologic malignancy, is not well understood. Here, we perform comprehensive multi-platform omics analyses, including integrated analysis, and immune monitoring on primary and metastatic sites from highly clinically annotated HGSC samples based on a laparoscopic triage algorithm from patients who underwent complete gross resection (R0) or received neoadjuvant chemotherapy (NACT) with excellent or poor response. We identify significant distinct molecular abnormalities and cellular changes and immune cell repertoire alterations between the groups, including a higher rate of NF1 copy number loss, and reduced chromothripsis-like patterns, higher levels of strong-binding neoantigens, and a higher number of infiltrated T cells in the R0 versus the NACT groups., Graphical Abstract, In Brief High-grade serous ovarian cancer (HGSC) patients with no gross residual disease (R0) after primary surgery have the greatest improvement in clinical outcomes. A deep understanding of molecular and cellular heterogeneity of HGSC is lacking. Findings by Lee et al. highlight major molecular and cellular differences between clinically defined subgroups of HGSC.

Harnessing the immune response to tumor antigens in the form of autoantibodies, which occurs early during tumor development, has relevance to the detection of cancer at early stages. We conducted an initial screen of antigens associated with an autoantibody response in serous ovarian cancer using recombinant protein arrays. The top 25 recombinants that exhibited increased reactivity with cases compared to controls revealed TP53 and MYC, which are ovarian cancer driver genes, as major network nodes. A mass spectrometry based independent analysis of circulating immunoglobulin (Ig)-bound proteins in ovarian cancer and of ovarian cancer cell surface MHC-II bound peptides also revealed a TP53&ndash, MYC related network of antigens. Our findings support the occurrence of a humoral immune response to antigens linked to ovarian cancer driver genes that may have utility for early detection applications.

There are no FDA approved screening tools for detecting ovarian cancer in the general population. The two best known ovarian cancer biomarkers, CA125 and HE4, are neither adequately sensitive nor specific when used alone to screen the general population for early stage disease. By using a combination of protein biomarkers for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the polymerase chain reaction with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high throughput quantification. We analyzed one microliter of serum from 61 women with advanced stage high grade serous ovarian cancer and compared the values obtained to 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with previously measured clinical values for CA125 (correlation coefficient of 0.91). CA125 and HE4 were detected at low levels in samples from healthy women, while higher levels were observed in the ovarian cancer cases. We identified 52 proteins that differed significantly (p < 0.006) between ovarian cancer and healthy samples; several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. However, by adding five proteins to CA125, we increased the assay sensitivity to 98.4%, while holding the specificity fixed at 98%. Our data demonstrate that the Proseek technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Citation Format: Amy P.N. Skubitz, Kristin L.M. Boylan, Kate Geschwind, Qing Cao, Timothy K. Starr, Melissa A. Geller, Joseph Celestino, Robert C. Bast Jr., Karen H. Lu, and Joseph S. Koopmeiners. DEVELOPMENT OF A MULTI-PROTEIN CLASSIFIER FOR OVARIAN CANCER DETECTION BY SIMULTANEOUS MEASUREMENT OF 92 SERUM PROTEINS ON PROSEEK MULTIPLEX ONCOLOGY II PLATES [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr AP08.

The best known ovarian cancer biomarker, CA125, is neither adequately sensitive nor specific for screening the general population. By using a combination of proteins for screening, it may be possible to increase the sensitivity and specificity over CA125 alone. In this study, we used Proseek Multiplex Oncology II plates to simultaneously measure the expression of 92 cancer-related proteins in serum using proximity extension assays. This technology combines the sensitivity of the PCR with the specificity of antibody-based detection methods, allowing multiplex biomarker detection and high-throughput quantification. We analyzed 1 μL of sera from each of 61 women with ovarian cancer and compared the values obtained with those from 88 age-matched healthy women. Principle component analysis and unsupervised hierarchical clustering separated the ovarian cancer patients from the healthy, with minimal misclassification. Data from the Proseek plates for CA125 levels exhibited a strong correlation with clinical values for CA125. We identified 52 proteins that differed significantly (P < 0.006) between ovarian cancer and healthy samples, several of which are novel serum biomarkers for ovarian cancer. In total, 40 proteins had an estimated area under the ROC curve of 0.70 or greater, suggesting their potential to serve as biomarkers for ovarian cancer. CA125 alone achieved a sensitivity of 93.4% at a specificity of 98%. By adding the Oncology II values for five proteins to CA125 in a multiprotein classifier, we increased the assay sensitivity to 98.4% at a specificity of 98%, thereby improving the sensitivity and specificity of CA125 alone.

BACKGROUND Liver kinase B1 (LKB1) is a serine/threonine kinase that functions as a tumor suppressor and regulates cell polarity, proliferation, and metabolism. Mutations in LKB1 are associated with Peutz-Jeghers syndrome as well as sporadic cervical and lung cancers. Although LKB1-null mice develop invasive endometrial cancers, the role and regulation of LKB1 in the pathogenesis of human endometrial cancer are not well defined and are the focus of these studies. METHODS LKB1 protein and messenger RNA (mRNA) expression levels were evaluated in high-grade and low-grade endometrioid endometrial cancer (EEC) and cell lines by reverse transcriptase-polymerase chain reaction analysis, Western blot analysis, and immunohistochemistry. Mutational and promoter analyses of the LKB1 gene (serine/threonine kinase 11 [STK11]) were performed to identify the mechanisms that contribute to the loss of LKB1 in high-grade EEC. RESULTS Analysis of the LKB1 gene in low-grade and high-grade EECs revealed no genetic mutations, suggesting that alterations in LKB1 transcription may be responsible for LKB1 protein loss in high-grade EEC. Analysis of the LKB1 promoter revealed 4 putative tumor protein 53 (p53) binding sites. Quantitative chromatin immunoprecipitation demonstrated that p53 bound directly to 1 of these sites and increased LKB1 promoter activity 140-fold. LKB1 promoter activity, mRNA, and protein levels were suppressed after silencing of p53 with small interfering RNA and were elevated in cells that overexpressed p53. Levels of p53 mRNA and protein expression were decreased in high-grade EEC and were positively correlated with LKB1 protein levels (Spearman correlation, r=0.601; P

Objectives: Obesity is a major risk factor for endometrial cancer. We evaluated whether obesity exacerbates progression of endometrial hyperplasia (EH) using the PRCre/+ PTENflox/+ mouse model and examined if the type 2 diabetes drug, metformin, could prevent EH. Methods: Twenty obese (PRCre/+ PTENflox/+) mice were maintained on a high-fat diet, while 20 lean mice ate a matching low-fat diet. Ten mice from each group received metformin (1,000 mg/day) in drinking water. Mice were euthanized at 26 weeks. Uterine tissue was scored for degree of EH. Immunohistochemical staining for Ki67 was used to evaluate cellular proliferation. Markers of PI3K/AKT/mTOR activity were evaluated by immunohistochemistry using activation-specific antibodies. Serum adiponectin was quantified by ELISA. Results: Obesity had no effect on the extent of EH in (PRCre/+ PTENflox/+) mice. While metformin significantly altered circulating adiponectin levels in obese and lean animals, it had no effect on EH. There were no differences in endometrial proliferation as measured by Ki67 staining. Neither obesity nor metformin altered PI3K/AKT/mTOR activity in these animals. Conclusions: Weight and metformin did not affect the severity of EH resulting from PTEN inactivation. Alternative mouse models of early endometrial cancer are required for preclinical cancer prevention studies.

Background: Early detection of ovarian cancer promises to reduce mortality. At present, only 20 percent of ovarian cancer is found in early stage (I-II). CA125 is found in sera from approximately 60% of patients with early stage disease. Greater sensitivity could be observed with a panel of blood tests. Methods: A panel of 10 antigen biomarkers (MIF, Leptin, IL-6, IL-8, TNFa, OPN, FGF2, HE4, TGFa and a panel of autoantibodies (AAbs) against 12 antigens (IL-8, MDM2, c-myc, PLAT, EpCAM, HOXA7, ENO1, PDI, HSPA5, HSPA8, ANXA2, Cathepsin D) were analyzed in sera of 77 ovarian cancer patients with early stage (I-II), 50 patients with late stage (III-IV), and 216 healthy women from the Normal Risk Ovarian Cancer Screening Study (NROSS) using Luminex-based immunoassays. Serum levels of serum tumor marker CA-125 were routinely measured in all patients using a Roche assay. The most promising markers (CA125, MIF, OPN, and anti-IL-8 autoantibodies were validated using an independent panel with sera from 69 early stage and 50 late ovarian cancer patients and 200 healthy controls. Result: Serum level of CA125, MIF, OPN and IL-8 AAb were elevated in early stage (I-II) and late stage (III-IV) ovarian cancer patients compared with healthy controls. Analyzing the positive biomarkers in combination with CA125 increased detection of early stage disease from 62% with CA125 alone to 92% a panel of CA125, MIF, OPN and IL-8 AAb at 98% specificity. For patients with late stage disease sensitivity increased from 90% to 98% with the panel. Complementarity of CA125 with MIF, OPN and IL-8 AAb was confirmed with an independent validation set, where sensitivity for early stage disease was improved from 84% to 91% at 98% specificity. Conclusion: MIF, OPN and IL8 AAb could be used in combination with CA125 to distinguish ovarian cancer patients from health controls with high sensitivity. Citation Format: Jing Guo, Wei-lei Yang, Joseph Celestino, Karen Lu, Anna E. Lokshin, Zhen Lu, Robert C. Bast. Macrophage inhibitory factor (MIF), osteopontin (OPN) and anti-interleukin-8 (IL-8) autoantibodies (AAb) complement CA125 for detection of early-stage ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 912.