Disease progression, survival, and molecular disparities in Black and White patients with endometrioid endometrial carcinoma in real-world registries and GOG/NRG oncology randomized phase III clinical trials

OBJECTIVE

Investigate racial disparities in outcomes and molecular features in Black and White patients with endometrioid endometrial carcinoma (EEC).

METHODS

Black and White patients diagnosed with EEC who underwent hysterectomy ± adjuvant treatment in SEER, National Cancer Database (NCDB), the Genomics Evidence Neoplasia Information Exchange (GENIE) project (v.13.0), and eight NCI-sponsored randomized phase III clinical trials (RCTs) were studied. Hazard ratio (HR) and 95% confidence interval (CI) were estimated for cancer-related death (CRD), non-cancer death (NCD), and all-cause death.

RESULTS

Black (n = 4397) vs. White (n = 47,959) patients in SEER had a HR (95% CI) of 2.04 (1.87-2.23) for CRD and 1.22 (1.09-1.36) for NCD. In NCDB, the HR (95% CI) for death in Black (n = 13,468) vs. White (n = 155,706) patients was 1.52 (1.46-1.58) dropping to 1.29 (1.23-1.36) after propensity-score matching for age, comorbidity, income, insurance, grade, stage, LVSI, and treatment. In GENIE, Black (n = 109) vs. White (n = 1780) patients had fewer PTEN, PIK3R1, FBXW7, NF1, mTOR, CCND1, and PI3K-pathway-related gene mutations. In contrast, TP53 and DNA-repair-related gene mutation frequency as well as tumor mutational burden-high status were similar in Black and White patients. In RCTs, Black (n = 187) vs. White (n = 2877) patients were more likely to have advanced or recurrent disease, higher grade, worse performance status and progressive disease. Risk of death in Black vs. White patients in RCTs was 2.19 (1.77-2.71) persisting to 1.32 (1.09-1.61) after matching for grade, stage, and treatment arm while balancing age and performance status.

CONCLUSIONS

Differences exist in clinical presentation, outcomes, and molecular features in Black vs. White patients with EEC in real-world registries and RCTs. Targeted-drug development, strategies to modify social determinants, and diverse inclusion in RCTs are approaches to reduce disparities.

Quantitative proteomic analysis of HER2 protein expression in PDAC tumors

Metastatic pancreatic adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States, with a 5-year survival rate of only 11%, necessitating identification of novel treatment paradigms. Tumor tissue specimens from patients with PDAC, breast cancer, and other solid tumor malignancies were collected and tumor cells were enriched using laser microdissection (LMD). Reverse phase protein array (RPPA) analysis was performed on enriched tumor cell lysates to quantify a 32-protein/phosphoprotein biomarker panel comprising known anticancer drug targets and/or cancer-related total and phosphorylated proteins, including HER2Total, HER2Y1248, and HER3Y1289. RPPA analysis revealed significant levels of HER2Total in PDAC patients at abundances comparable to HER2-positive (IHC 3+) and HER2-low (IHC 1+ /2+ , FISH-) breast cancer tissues, for which HER2 screening is routinely performed. These data support a critical unmet need for routine clinical evaluation of HER2 expression in PDAC patients and examination of the utility of HER2-directed antibody-drug conjugates in these patients.

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Immuno-Molecular Targeted Therapy Use and Survival Benefit in Patients with Stage IVB Cervical Carcinoma in Commission on Cancer®-Accredited Facilities in the United States

PURPOSE

To investigate IMT use and survival in real-world stage IVB cervical cancer patients outside randomized clinical trials.

METHODS

Patients diagnosed with stage IVB cervical cancer during 2013-2019 in the National Cancer Database and treated with chemotherapy (CT) ± external beam radiation (EBRT) ± intracavitary brachytherapy (ICBT) ± IMT were studied. The adjusted hazard ratio (AHR) and 95% confidence interval (CI) for risk of death were estimated in patients treated with vs. without IMT after applying propensity score analysis to balance the clinical covariates.

RESULTS

There were 3164 evaluable patients, including 969 (31%) who were treated with IMT. The use of IMT increased from 11% in 2013 to 46% in 2019. Age, insurance, facility type, sites of distant metastasis, and type of first-line treatment were independently associated with using IMT. In propensity-score-balanced patients, the median survival was 18.6 vs. 13.1 months for with vs. without IMT (p < 0.001). The AHR was 0.72 (95% CI = 0.64-0.80) for adding IMT overall, 0.72 for IMT + CT, 0.66 for IMT + CT + EBRT, and 0.69 for IMT + CT + EBRT + ICBT. IMT-associated survival improvements were suggested in all subgroups by age, race/ethnicity, comorbidity score, facility type, tumor grade, tumor size, and site of metastasis.

CONCLUSIONS

IMT was associated with a consistent survival benefit in real-world patients with stage IVB cervical cancer.

Survival disparities in non-Hispanic Black and White cervical cancer patients vary by histology and are largely explained by modifiable factors

PURPOSE

We investigated racial disparities in survival by histology in cervical cancer and examined the factors contributing to these disparities.

METHODS

Non-Hispanic Black and non-Hispanic White (hereafter known as Black and White) patients with stage I-IV cervical carcinoma diagnosed between 2004 and 2017 in the National Cancer Database were studied. Survival differences were compared using Cox modeling to estimate hazard ratio (HR) or adjusted HR (AHR) and 95% confidence interval (CI). The contribution of demographic, socioeconomic and clinical factors to the Black vs White differences in survival was estimated after applying propensity score weighting in patients with squamous cell carcinoma (SCC) or adenocarcinoma (AC).

RESULTS

This study included 10,111 Black and 43,252 White patients with cervical cancer. Black patients had worse survival than White cervical cancer patients (HR = 1.40, 95% CI = 1.35-1.45). Survival disparities between Black and White patients varied significantly by histology (HR = 1.20, 95% CI = 1.15-1.24 for SCC; HR = 2.32, 95% CI = 2.12-2.54 for AC, interaction p < 0.0001). After balancing the selected demographic, socioeconomic and clinical factors, survival in Black vs. White patients was no longer different in those with SCC (AHR = 1.01, 95% CI 0.97-1.06) or AC (AHR = 1.09, 95% CI = 0.96-1.24). In SCC, the largest contributors to survival disparities were neighborhood income and insurance. In AC, age was the most significant contributor followed by neighborhood income, insurance, and stage. Diagnosis of AC (but not SCC) at ≥65 years old was more common in Black vs. White patients (26% vs. 13%, respectively).

CONCLUSIONS

Histology matters in survival disparities and diagnosis at ≥65 years old between Black and White cervical cancer patients. These disparities were largely explained by modifiable factors.

Racial, ethnic and country of origin disparities in aggressive endometrial cancer histologic subtypes

OBJECTIVE

This study investigated the risk of an aggressive endometrial cancer (EC) diagnosis by race, ethnicity, and country of origin to further elucidate histologic disparities in non-Hispanic Black (NHB), Hispanic, Asian/Pacific Islander (API), American Indian/Alaskan Native (AIAN) vs. non-Hispanic White (NHW) patients, particularly in Hispanic or API subgroups.

METHODS

Patient diagnosed between 2004 and 2020 with low grade (LG)-endometrioid endometrial cancer (ECC) or an aggressive EC including grade 3 EEC, serous carcinoma, clear cell carcinoma, mixed epithelial carcinoma, or carcinosarcoma in the National Cancer Database were studied. The odds ratio (OR) and 95% confidence interval (CI) for diagnosis of an aggressive EC histology was estimated using logistic modeling.

RESULTS

There were 343,868 NHW, 48,897 NHB, 30,013 Hispanic, 15,015 API and 1646 AIAN patients. The OR (95% CI) for an aggressive EC diagnosis was 3.07 (3.01-3.13) for NHB, 1.08 (1.06-1.11) for Hispanic, 1.17 (1.13-1.21) for API and 1.07 (0.96-1.19) for AIAN, relative to NHW patients. Subset analyses by country of origin illustrated the diversity in the OR for an aggressive EC diagnosis among Hispanic (1.18 for Mexican to 1.87 for Dominican), Asian (1.14 Asian Indian-Pakistani to 1.48 Korean) and Pacific Islander (1.00 for Hawaiian to 1.33 for Samoan) descendants. Hispanic, API and AIAN patients were diagnosed 5-years younger that NHW patients, and the risk for an aggressive EC histology were all significantly higher than NHW patients after correcting for age. Insurance status was another independent risk factor for aggressive histology.

CONCLUSIONS

Risk of an aggressive EC diagnosis varied by race, ethnicity, and country of origin. NHB patients had the highest risk, followed by Dominican, South/Central American, Cuban, Korean, Thai, Vietnamese, and Filipino descendants.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling

BACKGROUND

Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics.

METHODS

Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor.

RESULTS

LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ).

CONCLUSIONS

Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

Deep learning-based segmentation of multisite disease in ovarian cancer

PURPOSE

To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.

METHODS

A deep learning model for the two most common disease sites of high-grade serous ovarian cancer lesions (pelvis/ovaries and omentum) was developed and compared against the well-established "no-new-Net" framework and unrevised trainee radiologist segmentations. A total of 451 CT scans collected from four different institutions were used for training (n = 276), evaluation (n = 104) and testing (n = 71) of the methods. The performance was evaluated using the Dice similarity coefficient (DSC) and compared using a Wilcoxon test.

RESULTS

Our model outperformed no-new-Net for the pelvic/ovarian lesions in cross-validation, on the evaluation and test set by a significant margin (p values being 4 × 10-7, 3 × 10-4, 4 × 10-2, respectively), and for the omental lesions on the evaluation set (p = 1 × 10-3). Our model did not perform significantly differently in segmenting pelvic/ovarian lesions (p = 0.371) compared to a trainee radiologist. On an independent test set, the model achieved a DSC performance of 71 ± 20 (mean ± standard deviation) for pelvic/ovarian and 61 ± 24 for omental lesions.

CONCLUSION

Automated ovarian cancer segmentation on CT scans using deep neural networks is feasible and achieves performance close to a trainee-level radiologist for pelvic/ovarian lesions.

RELEVANCE STATEMENT

Automated segmentation of ovarian cancer may be used by clinicians for CT-based volumetric assessments and researchers for building complex analysis pipelines.

KEY POINTS

• The first automated approach for pelvic/ovarian and omental ovarian cancer lesion segmentation on CT images has been presented. • Automated segmentation of ovarian cancer lesions can be comparable with manual segmentation of trainee radiologists. • Careful hyperparameter tuning can provide models significantly outperforming strong state-of-the-art baselines.

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients' tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

The murine metastatic microenvironment of experimental brain metastases of breast cancer differs by host age in vivo: a proteomic study

Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients.

Automated imaging and identification of proteoforms directly from ovarian cancer tissue

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.

Brain proteomic atlas of alcohol use disorder in adult males

Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABAB receptor and opioid receptors and may lead to the identification of other potential targets. These results improve our understanding of the molecular alterations of AUD across brain regions that are associated with the development and maintenance of AUD. Proteomic data from this study is publicly available at www.lmdomics.org/AUDBrainProteomeAtlas/ .

Metronomic dosing of ovarian cancer cells with the ATR inhibitor AZD6738 leads to loss of CDC25A expression and resistance to ATRi treatment

OBJECTIVE

ATR kinase inhibitors promote cell killing by inducing replication stress and through potentiation of genotoxic agents in gynecologic cancer cells. To explore mechanisms of acquired resistance to ATRi in ovarian cancer, we characterized ATRi-resistant ovarian cancer cells generated by metronomic dosing with the clinical ATR inhibitor AZD6738.

METHODS

ATRi-resistant ovarian cancer cells (OVCAR3 and OV90) were generated by dosing with AZD6738 and assessed for sensitivity to Chk1i (LY2603618), PARPi (Olaparib) and combination with cisplatin or a CDK4/6 inhibitor (Palbociclib). Models were characterized by diverse methods including silencing CDC25A in OV90 cells and assessing impact on ATRi response. Serum proteomic analysis of ATRi-resistant OV90 xenografts was performed to identify circulating biomarker candidates of ATRi-resistance.

RESULTS

AZD6738-resistant cell lines are refractory to LY2603618, but not to Olaparib or combinations with cisplatin. Cell cycle analyses showed ATRi-resistant cells exhibit G1/S arrest following AZD6738 treatment. Accordingly, combination with Palbociclib confers resistance to AZD6738. AZD6738-resistant cells exhibit altered abundances of G1/S phase regulatory proteins, including loss of CDC25A in AZD6738-resistant OV90 cells. Silencing of CDC25A in OV90 cells confers resistance to AZD6738. Serum proteomics from AZD6738-resistant OV90 xenografts identified Vitamin D-Binding Protein (GC), Apolipoprotein E (APOE) and A1 (APOA1) as significantly elevated in AZD6738-resistant backgrounds.

CONCLUSIONS

We show that metronomic dosing of ovarian cancer cells with AZD6738 results in resistance to ATR/ Chk1 inhibitors, that loss of CDC25A expression represents a mechanism of resistance to ATRi treatment in ovarian cancer cells and identify several circulating biomarker candidates of CDC25A low, AZD6738-resistant ovarian cancer cells.

Integration of Multi-omic Data in a Molecular Tumor Board Reveals EGFR-Associated ALK-Inhibitor Resistance in a Patient With Inflammatory Myofibroblastic Cancer

Inflammatory myofibroblastic tumors (IMTs) are intermediate-grade mesenchymal neoplasms commonly characterized by chromosomal rearrangements causing constitutive activation of anaplastic lymphoma kinase (ALK) and/or ALK mutations causing reduced sensitivity to ALK tyrosine kinase inhibitors (TKI). We present a patient with an IMT who initially responded to first-line alectinib, but who later suffered disease relapse and presently survives with moderate residual disease after receiving second-line lorlatinib. Biopsy specimens were analyzed using next generation sequencing (DNA-seq and RNA-seq) and reverse phase protein microarray (RPPA) as part of an institutional Molecular Tumor Board (MTB) study. An EML4-ALK rearrangement and EGFR activation (pEGFRY1068) were present in both the primary and recurrent tumors, while a secondary ALK I1171N mutation was exclusive to the latter. EGFR signaling in the background of a secondary ALK mutation is correlated with reduced ALK TKI sensitivity in vitro, implicating an important mechanism of drug resistance development in this patient. The RPPA results also critically demonstrate that ALK signaling (ALKY1604) was not activated in the recurrent tumor, thereby indicating that standard-of-care use of third- or fourth-line ALK TKI would not likely be efficacious or durable. These results underscore the importance of real-time clinical integration of functional protein drug target activation data with NGS in the MTB setting for improving selection of patient-tailored therapy.

Abstract 5782: The dynamic immune behavior of primary and metastatic tumors of ovarian cancer

Background: Despite advances in cancer diagnosis and therapy, high-grade serous ovarian cancer (HGSC) is often diagnosed when spread to multiple intraperitoneal areas; it is prone to metastasize to adipose-rich tissues such as the omentum. To gain a deeper understanding of the molecular determinants of the HGSC milieu, we carried out a single-cell analysis of primary and metastatic tumors of HGSC. Thus, our aim is to identify molecular mechanisms that lead to immunosuppressive mechanisms of HGSC in primary and metastatic tumors of HGSC.

Methods: Fresh HGSC surgical samples from 19 patients were collected right after surgery, dissociated, and then frozen. For single-cells analysis, cells were sorted by a viability dye and CD45+/- populations followed by Single cell 10 × 3’v3 protocol (10X Genomics) and sequenced using the NovaSeq6000 S2 sequencer. Cell Ranger toolkit v3.1.0 (10x Genomics) was applied for data processing, followed by further downstream analysis using multiple packages from R Package Seurat.

Results: To elucidate the cellular heterogeneity of HGSC, we analyzed 100,480 cells, including epithelial, lymphoid, and myeloid populations; these were identified and represented across all patients. We explored the epithelial compartment further, including a total of 21,144 cells. Given the importance of metastatic lesions for the treatment and outcome of patients with HGSC, we examined expression programs among primary and omentum tumors as well treated and untreated tumors. The major differences between primary and omental metastatic tumors included enrichment of EMT pathways and angiogenesis, as well as a decrease in the IFNα and IFNγ response in the omentum. IFNα and IFNγ response pathways were also upregulated in primary treated (P-NACT) tumors, when compared with primary untreated (P-UT) tumors. To explore the immune compartment, we clustered the immune cells across patients in 28 sub-clusters, including 19 sub-clusters of T-cells and Natural Killer cells. Altogether, the immune infiltration on P-UT indicated an immune infiltrate environment and the composition of P-UT was highly enriched in lymphoid cells with a late stage of differentiation. This finding was also demonstrated by the analysis of T cell trajectories, with a clear definition that CD8 and CD4 cells from P-UT tumors are in a late/final and exhausted stage of differentiation, while post-NACT tumors (independent of tissue type) are in early stages (naïve/central memory). The measurement of a dysfunctional score showed that P-UT tumors have the highest scores, indicating a potential increase in tumor reactivity in P-UT tumors.

Conclusions: Collectively, these data indicate that HGSC primary and omentum tumors are very distinct niches for immune cells, with primary being much more dysfunctional than omentum tissue, which could indicate that the application of immunotherapies would have different impacts in variable niches of HGSC.

Citation Format: Elaine Stur, Fuduan Peng, Pang-ning Teng, Emine Bayraktar, Min Hu, Sara Corvigno, David J. Brown, Sanghoon Lee, Kathleen N. Moore, Nicholas W. Bateman, Kathleen M. Darcy, George L. Maxwell, Thomas Conrads, Nicole Fleming, Nicholas Navin, Linghua Wang, Anil K. Sood. The dynamic immune behavior of primary and metastatic tumors of 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 5782.

Factors Associated With Survival Disparities Between Non-Hispanic Black and White Patients With Uterine Cancer

Importance

Disparities in survival exist between non-Hispanic Black (hereafter, Black) and non-Hispanic White (hereafter, White) patients with uterine cancer.

Objective

To investigate factors associated with racial disparities in survival between Black and White patients with uterine cancer.

Design, Setting, and Patients

This cohort study used data from the National Cancer Database on 274 838 Black and White patients who received a diagnosis of uterine cancer from January 1, 2004, to December 31, 2017, with follow-up through December 2020. Statistical analysis was performed in July 2022.

Main Outcomes and Measures

Overall survival by self-reported race and evaluation of explanatory study factors associated with hazard ratio (HR) reduction for Black vs White patients. A propensity scoring approach was applied sequentially to balance racial differences in demographic characteristics, comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, and treatment.

Results

The study included 32 230 Black female patients (mean [SD] age at diagnosis, 63.8 [10.0] years) and 242 608 White female patients (mean [SD] age at diagnosis, 63.5 [10.5] years) and had a median follow-up of 74.0 months (range, 43.5-113.8 months). Black patients were more likely than White patients to have low income (44.1% vs 14.0%), be uninsured (5.7% vs 2.6%), present with nonendometrioid histologic characteristics (46.1% vs 21.6%), have an advanced disease stage (34.1% vs 19.8%), receive first-line chemotherapy (33.8% vs 18.2%), and have worse 5-year survival (58.6% vs 78.5%). Among patients who received a diagnosis at younger than 65 years of age, the HR for death for Black vs White patients was 2.43 (95% CI, 2.34-2.52) in a baseline demographic-adjusted model and 1.29 (95% CI, 1.23-1.35) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 0.8%, 7.2%, 11.5%, 53.1%, 5.8%, 1.2%, and 20.4%, respectively, of the excess relative risk (ERR) among the younger Black vs White patients. Among patients 65 years or older, the HR for death for Black vs White patients was 1.87 (95% CI, 1.81-1.93) in the baseline model and 1.14 (95% CI, 1.09-1.19) after balancing other factors. Comorbidity score, neighborhood income, insurance status, histologic subtype, disease stage, treatment, and unexplained factors accounted for 3.0%, 7.5%, 0.0%, 56.2%, 10.6%, 6.9%, and 15.8%, respectively, of the ERR among Black vs White patients aged 65 years or older.

Conclusions and Relevance

This study suggests that histologic subtype was the dominant factor associated with racial survival disparity among patients with uterine cancer, while insurance status represented the main modifiable factor for women younger than 65 years. Additional studies of interactions between biology and social determinants of health are merited.

Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients.

Integrated multi-omic analysis of low-grade ovarian serous carcinoma collected from short and long-term survivors

BACKGROUND

Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors.

METHODS

Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed.

RESULTS

We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets.

CONCLUSIONS

This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC.

The genomic and immune landscape of long-term survivors of high-grade serous ovarian cancer

Fewer than half of all patients with advanced-stage high-grade serous ovarian cancers (HGSCs) survive more than five years after diagnosis, but those who have an exceptionally long survival could provide insights into tumor biology and therapeutic approaches. We analyzed 60 patients with advanced-stage HGSC who survived more than 10 years after diagnosis using whole-genome sequencing, transcriptome and methylome profiling of their primary tumor samples, comparing this data to 66 short- or moderate-term survivors. Tumors of long-term survivors were more likely to have multiple alterations in genes associated with DNA repair and more frequent somatic variants resulting in an increased predicted neoantigen load. Patients clustered into survival groups based on genomic and immune cell signatures, including three subsets of patients with BRCA1 alterations with distinctly different outcomes. Specific combinations of germline and somatic gene alterations, tumor cell phenotypes and differential immune responses appear to contribute to long-term survival in HGSC.

Proteomic alterations associated with residual disease in neoadjuvant chemotherapy treated ovarian cancer tissues

BACKGROUND

Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome for high-grade serous ovarian cancer (HGSOC) patients. Treatment of HGSOC patients with neoadjuvant chemotherapy, however, may select for tumor cells harboring alterations in hallmark cancer pathways including metastatic potential. This study assessed this hypothesis by performing proteomic analysis of matched, chemotherapy naïve and neoadjuvant chemotherapy (NACT)-treated HGSOC tumors obtained from patients who had suboptimal (R1, n = 6) versus optimal (R0, n = 14) debulking at interval debulking surgery (IDS).

METHODS

Tumor epithelium was harvested by laser microdissection from formalin-fixed, paraffin-embedded tissues from matched, pre- and post-NACT treated tumors for twenty HGSOC patients and analyzed by quantitative mass spectrometry-based proteomics.

RESULTS

Differential analysis of patient matched pre- and post-NACT treated tumors revealed proteins associated with cell survival and metabolic signaling to be significantly altered in post-NACT treated tumor cells. Comparison of pre-NACT treated tumors from suboptimal (R1) versus optimally (R0) debulked patients identified proteins associated with tumor cell viability and invasion signaling enriched in R1 patients. We identified five proteins altered between R1 and R0 patients in pre- NACT treated tumors that significantly correlated with PFS in an independent cohort of HGSOC patients, including Fermitin family homolog 2 (FERMT2), a protein elevated in R1 that correlated with disease progression in HGSOC patients (multivariate Cox HR = 1.65, Wald p = 0.022) and increased metastatic potential in solid-tumor malignancies.

CONCLUSIONS

This study identified distinct proteome profiles in patient matched pre- and post-NACT HGSOC tumors that correlate with NACT resistance and that may predict residual disease status at IDS that collectively warrant further pre-clinical investigation.

Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

IMPORTANCE

Despite 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.

OBJECTIVE

To develop and characterize a gross morphologic classification system for HGSOC.

DESIGN, SETTING, AND PARTICIPANTS

This 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.

EXPOSURES

Gross tumor morphologic characteristics.

MAIN OUTCOMES AND MEASURES

Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared.

RESULTS

Of 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 RELEVANCE

This 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.

Improving Risk Assessment for Metastatic Disease in Endometrioid Endometrial Cancer Patients Using Molecular and Clinical Features: An NRG Oncology/Gynecologic Oncology Group Study

Objectives: A risk assessment model for metastasis in endometrioid endometrial cancer (EEC) was developed using molecular and clinical features, and prognostic association was examined. Methods: Patients had stage I, IIIC, or IV EEC with tumor-derived RNA-sequencing or microarray-based data. Metastasis-associated transcripts and platform-centric diagnostic algorithms were selected and evaluated using regression modeling and receiver operating characteristic curves. Results: Seven metastasis-associated transcripts were selected from analysis in the training cohorts using 10-fold cross validation and incorporated into an MS7 classifier using platform-specific coefficients. The predictive accuracy of the MS7 classifier in Training-1 was superior to that of other clinical and molecular features, with an area under the curve (95% confidence interval) of 0.89 (0.80-0.98) for MS7 compared with 0.69 (0.59-0.80) and 0.71 (0.58-0.83) for the top evaluated clinical and molecular features, respectively. The performance of MS7 was independently validated in 245 patients using RNA sequencing and in 81 patients using microarray-based data. MS7 + MI (myometrial invasion) was preferrable to individual features and exhibited 100% sensitivity and negative predictive value. The MS7 classifier was associated with lower progression-free and overall survival (p ≤ 0.003). Conclusion: A risk assessment classifier for metastasis and prognosis in EEC patients with primary tumor derived MS7 + MI is available for further development and optimization as a companion clinical support tool.

Conditional estimates for uterine serous cancer: Tools for survivorship counseling and planning

OBJECTIVES

Develop conditional survival and risk-assessment estimates for uterine serous carcinoma (USC) overall and stratified by stage as tools for annual survivorship counseling and care planning.

METHODS

Patients in the National Cancer Data Base diagnosed between 2004 and 2014 with stage I-IV USC were eligible. Individuals missing stage or survival data or with multiple malignancies were excluded. Five-year conditional survival was estimated using the stage-stratified Kaplan-Meier method annually during follow-up. A standardized mortality ratio (SMR) estimated the proportion of observed to expected deaths in the U.S. adjusted for year, age, and race. The relationships between prognostic factors and survival were studied using multivariate Cox modeling at diagnosis and conditioned on surviving 5-years.

RESULTS

There were 14,575 participants, including 43% with stage I, 8% with stage II, 29% with stage III, and 20% with stage IV USC. Five-year survival at diagnosis vs. after surviving 5-years was 52% vs. 75% overall, 77% vs. 81% for stage I, 57% vs. 72% for stage II, 40% vs. 66% for stage III, and 17% vs. 60% for stage IV USC, respectively (P < 0.0001). Incremental improvements in 5-year conditional survival and reductions in SMR tracked with annual follow-up and higher stage. The adjusted risk of death at diagnosis vs. after surviving 5-years was 1.15 vs. 1.40 per 5-year increase of age, 1.26 vs. 1.68 for Medicaid insurance, 3.92 vs. 2.48 for stage III disease, and 6.65 vs. 2.79 for stage IV disease, respectively (P < 0.0001).

CONCLUSION

In USC, the evolution of conditional survival permits annual reassessments of prognosis to tailor survivorship counseling and care planning.

Whole-Genome Sequencing Identifies PPARGC1A as a Putative Modifier of Cancer Risk in BRCA1/2 Mutation Carriers

While BRCA1 and BRCA2 mutations are known to confer the largest risk of breast cancer and ovarian cancer, the incomplete penetrance of the mutations and the substantial variability in age at cancer onset among carriers suggest additional factors modifying the risk of cancer in BRCA1/2 mutation carriers. To identify genetic modifiers of BRCA1/2, we carried out a whole-genome sequencing study of 66 ovarian cancer patients that were enriched with BRCA carriers, followed by validation using data from the Pan-Cancer Analysis of Whole Genomes Consortium. We found PPARGC1A, a master regulator of mitochondrial biogenesis and function, to be highly mutated in BRCA carriers, and patients with both PPARGC1A and BRCA1/2 mutations were diagnosed with breast or ovarian cancer at significantly younger ages, while the mutation status of each gene alone did not significantly associate with age of onset. Our study suggests PPARGC1A as a possible BRCA modifier gene. Upon further validation, this finding can help improve cancer risk prediction and provide personalized preventive care for BRCA carriers.

Peptide ancestry informative markers in uterine neoplasms from women of European, African, and Asian ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with disease pathogenesis. Nonsynonymous single-nucleotide polymorphisms encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis identified that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R² = 0.99). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues combined resulted in the quantitation of 62 pAIMs that correlate with patient race and genotype-confirmed ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. pAIMs will support generalized proteoancestry assessment as well as efforts investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

Obesity and altered angiogenic-related gene expression in endometrial cancer

OBJECTIVES

Evaluate association between obesity and angiogenic-related gene expression in endometrial cancer (EC). Evaluate interaction between diet and metformin on angiogenic-related gene expression.

METHODS

We evaluated the association between 168 human angiogenic-related genes and body mass index (BMI) in the TCGA Uterine Corpus Endometrial Carcinoma cohort (endometrioid endometrial cancer (EEC) cohort n = 290, and copy number high cohort n = 55), an independent validation cohort from Gynecologic Cancer Center of Excellence (GYN-COE) (n = 62) and corresponding 185 homologous mouse genes in an LKB1fl/flp53fl/fl mouse model of EC (n = 20). Mice received 60% of calories from fat in a high-fat diet (HFD), mimicking diet-induced obesity, versus 10% of calories from fat in a low-fat diet (LFD). After tumor growth, HFD (n = 5) and LFD (n = 5) mice were treated with metformin (200 mg/kg/day) or control. Whole transcriptome analysis of mouse tumors was performed using RNA-Seq.

RESULTS

At a false-discovery rate of 10%, twenty-one angiogenic-related genes were differentially expressed with respect to BMI when adjusting for grade in the TCGA EEC cohort. Evaluation of these genes in the mouse model control group revealed association between increased Edil3 expression in HFD versus LFD mice (2.5-fold change (FC); unadjusted p = 0.03). An interaction was observed for expression of Edil3 between diet and metformin treatment (unadjusted p = 0.009). Association between BMI and increased expression of EDIL3 was validated in one of four EDIL3 probesets in the GYN-COE cohort (p = 0.0011, adjusted p = 0.0342).

CONCLUSIONS

Obesity may promote tumor progression via differential modulation of angiogenic pathways in EEC. Our exploratory findings demonstrated that EDIL3 may be a candidate gene of interest.

Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor "purity." Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

Standardization and harmonization of distributed multi-center proteotype analysis supporting precision medicine studies

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

Abstract 5893: Comprehensive proteogenomic analysis and classification of lung adenocarcinoma

Lung adenocarcinoma is a highly lethal tumor that displays extensive molecular heterogeneity of which deep characterization may drive therapeutic development and improve clinical outcomes. Through the Applied Proteogenomics Organizational Learning and Outcomes (APOLLO) research network, we utilized five molecular profiling technologies (DNA whole genome sequencing, RNA sequencing, total and phospho-proteomics by mass spectrometry, and reverse phase protein arrays [RPPA]) to characterize a longitudinally-annotated cohort of 87 lung adenocarcinomas. Through whole genome sequencing, we identified molecular signatures from patterns of somatic SNVs, indels, and large structural alterations that stratified tumors into three groups associated with patient smoke exposures. We also identified TP53, EGFR, KRAS, and STK11 as recurrently mutated genes, which together represent 80% of the cohort, in addition to genes mutated in smaller cohort subsets (e.g. RBM10), fusion genes, and pathogenic germline variants. To characterize tumor proteomes, we quantified &gt;7,000 proteins and &gt;10,000 phosphopeptides by mass spectrometry and &gt;300 species by RPPA. Matched RNAs and proteins were typically positively correlated across samples (median ρ = 0.49). Through quantitative trait loci analyses, we identified genes whose RNA and protein expression levels were significantly modified by somatic mutations. We then classified tumors into RNA expression subtypes and found coordinated proteogenomic alterations and distinct clinical associations: terminal respiratory unit subtype – EGFR mutations and RNA/protein overexpression, acinar histology, non-smokers; proximal-proliferative subtype – STK11 mutations and RNA/protein underexpression, high smoking signature; proximal-inflammatory subtype – high tumor mutational burden. We also identified phospho-peptide signatures associated with these subtypes, including downregulation of CDK1/2 targets in terminal respiratory unit tumors. Protein co-expression network analysis discovered biologically-diverse pathway activities of the RNA expression subtypes. To interrogate somatic mutations in the context of molecular pathways, we projected DNA alterations onto known interaction networks and identified four subtypes with markedly distinct proteomic and microenvironment characteristics. Finally, several molecular characteristics were found to significantly predict patient outcomes, including RNA expression subtype classification against metastasis-free survival. Thus, our integrative, proteogenomic characterization of lung adenocarcinoma uncovered novel tumor biology and identified potential molecular markers for predicting patient outcomes. The views expressed in this abstract are solely of the authors and do not reflect the official policy of the Departments of Army/Navy/Air Force, Department of Defense, USUHS, HJF, or U.S. Government.

Citation Format: Anthony R. Soltis, Nicholas W. Bateman, Thomas P. Conrads, Clifton L. Dalgard, Hai Hu, Teri J. Franks, Jianfang Liu, Daoud Meerzaman, Emanuel F. Petricoin, Qingrong Chen, Chunhua Yan, Xijun Zhang, Clesson E. Turner, The APOLLO Research Network, Craig D. Shriver, Christopher A. Moskaluk, Robert F. Browning, Matthew D. Wilkerson. Comprehensive proteogenomic analysis and classification of lung adenocarcinoma [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 5893.

Abstract 6018: The perfused 3DKUBE™ rare tumor assay models in vivo drug response

Models that accurately reflect patient drug response are essential for the clinical design of personalized treatment plans and necessary for preclinical drug development. The advancement of predictive models for rare tumor types is impeded in part, by the relative scarcity of fresh tumor tissue available for study. To address the problem of tissue availability we have developed a label-free, combined functional and chemical selection method for the isolation of rare tumor cancer stem cells (CSC) and circulating tumor cells (CTC) from primary patient tissue and blood. Enriched cells were expanded as 3D microtumors under optimized conditions, validated as CSC through in vivo tumorigenesis studies, and characterized by correlative genomic, proteomic/phosphoproteomic, and phenomic analysis. We found isolation and expansion by this method yielded a source of primary cells suitable for live, cell-based predictive drug screening in multiple rare tumor derived models of neuroendocrine and mesenchymal origin, including locally or regionally advanced and metastatic SCLC, recurrent Merkel Cell Carcinoma, recurrent osteosarcoma and dermatofibrosarcoma protuberans. The 3DKUBE™ rare tumor assay was performed using validated CSCs cultured as perfused 3D microtumors (pMTs). Drug studies using the perfused, 3DKUBE™ rare tumor assay modeled individual patient response better than CSC-based or 3D static microtumor-based drug screens and thus demonstrate the effectiveness of this platform for predictive modeling of individual patient drug response. Taken together, this system provides a means of performing ex vivo drug response experiments on very small tissue samples, including core biopsies, with relevant results for patients.

Citation Format: Melissa Millard, Kathryn M. Appleton, Ashley Elrod, Nicholas W. Bateman, Tamara Abulez, Kelly Conrads, Brian Hood, Thomas P. Conrads, Lillia M. Holmes, Teresa M. DesRochers. The perfused 3DKUBE™ rare tumor assay models in vivo drug response [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 6018.

Abstract 2510: High-depth whole genome sequencing of clinically-annotated high-grade serous ovarian cancers

Background: Prior molecular characterization efforts for high-grade serous ovarian cancer (HGSOC) were restricted to those who had upfront surgical debulking with variable treatment paradigms. Thus, we sought to examine molecular and cellular differences between clinically defined groups (tumor tissues from patients who had complete gross resection (CGR) versus those who were triaged to neoadjuvant chemotherapy (NACT) and experienced either excellent or poor response.

Methods: Tumor biopsies were collected from three patient groups managed under a systematic surgical algorithm: CGR after primary surgery (R0, n=10); poor tumor response to NACT (NACT-PR, n=10); excellent tumor response to NACT (NACT-ER, n=10). Primary and multiple metastatic tumor sites per each patient were obtained pre-treatment and subjected to comprehensive omics analyses including high-pass whole-genome (WGS) and targeted deep DNA sequencing.

Results: An average of 71 nonsynonymous somatic mutations from each sample for 75 samples with high-purity tumors (≥75%) by WGS were identified from each sample for the entire cohort. Fourteen ovarian-cancer-associated genes were found mutated in our patient cohort and, as expected, the most frequently mutated gene was TP53 in both primary and metastatic sites in all three groups. TP53 nonsense mutations were exclusively identified in the NACT-ER (36.0%) and NACT-PR groups (15.4%), while in the R0 group most TP53 mutations were missense mutations (62.5%). Nonsense mutations in CSMD3 and PIK3CA were exclusively identified in both primary and metastatic sites in the NACT-PR group. The most frequent copy number variations (CNVs) in the R0 were copy number gain/loss of CSMD3 (67%) and copy number loss of NF1 (54%) and CDK12 (50%) in both primary and metastatic sites. Interestingly, copy number losses of NF1 were significantly lower in the NACT groups (18%, p=0.002), especially in the NACT-PR (8%, p=0.0004), when compared to the R0 group (54%). We also identified significant less observation of chromothripsis-like patterns, and a significantly higher level of strong-binding neoantigens in the R0 than in the NACT groups.

Conclusions: Our findings using HGSOC samples obtained from patients treated on a prospective algorithm identified distinct molecular abnormalities, and could have prognostic and therapeutic implications for patients with HGSOC.

Citation Format: Sanghoon Lee, Li Zhao, Shannon N. Westin, Nicholas W. Bateman, Amir A. Jazaeri, Nicole D. Fleming, Karen H. Lu, Robert L. Coleman, Gordon B. Mills, Jianhua Zhang, Thomas P. Conrads, George L. Maxwell, P. Andrew Futreal, Anil K. Sood. High-depth whole genome sequencing of clinically-annotated high-grade serous ovarian cancers [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 2510.

Integration of proteomics with CT-based qualitative and radiomic features in high-grade serous ovarian cancer patients: an exploratory analysis

OBJECTIVES

To investigate the association between CT imaging traits and texture metrics with proteomic data in patients with high-grade serous ovarian cancer (HGSOC).

METHODS

This retrospective, hypothesis-generating study included 20 patients with HGSOC prior to primary cytoreductive surgery. Two readers independently assessed the contrast-enhanced computed tomography (CT) images and extracted 33 imaging traits, with a third reader adjudicating in the event of a disagreement. In addition, all sites of suspected HGSOC were manually segmented texture features which were computed from each tumor site. Three texture features that represented intra- and inter-site tumor heterogeneity were used for analysis. An integrated analysis of transcriptomic and proteomic data identified proteins with conserved expression between primary tumor sites and metastasis. Correlations between protein abundance and various CT imaging traits and texture features were assessed using the Kendall tau rank correlation coefficient and the Mann-Whitney U test, whereas the area under the receiver operating characteristic curve (AUC) was reported as a metric of the strength and the direction of the association. P values < 0.05 were considered significant.

RESULTS

Four proteins were associated with CT-based imaging traits, with the strongest correlation observed between the CRIP2 protein and disease in the mesentery (p < 0.001, AUC = 0.05). The abundance of three proteins was associated with texture features that represented intra-and inter-site tumor heterogeneity, with the strongest negative correlation between the CKB protein and cluster dissimilarity (p = 0.047, τ = 0.326).

CONCLUSION

This study provides the first insights into the potential associations between standard-of-care CT imaging traits and texture measures of intra- and inter-site heterogeneity, and the abundance of several proteins.

KEY POINTS

• CT-based texture features of intra- and inter-site tumor heterogeneity correlate with the abundance of several proteins in patients with HGSOC. • CT imaging traits correlate with protein abundance in patients with HGSOC.

Chemical inhibition of FBXO7 reduces inflammation and confers neuroprotection by stabilizing the mitochondrial kinase PINK1

Mitochondrial quality control is mediated by the PTEN-induced kinase 1 (PINK1), a cytoprotective protein that is dysregulated in inflammatory lung injury and neurodegenerative diseases. Here, we show that a ubiquitin E3 ligase receptor component, FBXO7, targets PINK1 for its cellular disposal. FBXO7, by mediating PINK1 ubiquitylation and degradation, was sufficient to induce mitochondrial injury and inflammation in experimental pneumonia. A computational simulation-based screen led to the identification of a small molecule, BC1464, which abrogated FBXO7 and PINK1 association, leading to increased cellular PINK1 concentrations and activities, and limiting mitochondrial damage. BC1464 exerted antiinflammatory activity in human tissue explants and murine lung inflammation models. Furthermore, BC1464 conferred neuroprotection in primary cortical neurons, human neuroblastoma cells, and patient-derived cells in several culture models of Parkinson's disease. The data highlight a unique opportunity to use small molecule antagonists that disrupt PINK1 interaction with the ubiquitin apparatus to enhance mitochondrial quality, limit inflammatory injury, and maintain neuronal viability.

Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer

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.

The impact of ultraviolet- and infrared-based laser microdissection technology on phosphoprotein detection in the laser microdissection-reverse phase protein array workflow

Reversible protein phosphorylation represents a key mechanism by which signals are transduced in eukaryotic cells. Dysregulated phosphorylation is also a hallmark of carcinogenesis and represents key drug targets in the precision medicine space. Thus, methods that preserve phosphoprotein integrity in the context of clinical tissue analyses are crucially important in cancer research. Here we investigated the impact of UV laser microdissection (UV LMD) and IR laser capture microdissection (IR LCM) on phosphoprotein abundance of key cancer signaling protein targets assessed by reverse-phase protein microarray (RPPA). Tumor epithelial cells from consecutive thin sections obtained from four high-grade serous ovarian cancers were harvested using either UV LMD or IR LCM methods. Phosphoprotein abundances for ten phosphoproteins that represent important drug targets were assessed by RPPA and revealed no significant differences in phosphoprotein integrity from those obtained using higher-energy UV versus the lower-energy IR laser methods.

Racial disparities in uterine and ovarian carcinosarcoma: A population-based analysis of treatment and survival

OBJECTIVE

To investigate racial disparities in uterine carcinosarcoma (UCS) and ovarian carcinosarcoma (OCS) in Commission on Cancer®-accredited facilities.

METHODS

Non-Hispanic Black (NHB) and non-Hispanic White (NHW) women in the National Cancer Database diagnosed with stage I-IV UCS or OCS between 2004 and 2014 were eligible. Differences by disease site or race were compared using Chi-square test and multivariate Cox analysis.

RESULTS

There were 2830 NHBs and 7366 NHWs with UCS, and 280 NHBs and 2586 NHWs with OCS. Diagnosis of UCS was more common in NHBs (11.5%) vs. NHWs (3.7%) and increased with age (P < .0001). OCS diagnosis remained <5% in both races and all ages. NHBs with UCS or OCS were more common in the South and more likely to have a comorbidity score ≥ 1, low neighborhood income and Medicaid or no insurance (P < .0001). Diagnosis at stage II-IV was more common in NHBs than NHWs with UCS but not OCS. NHBs with both UCS and OCS were less likely to undergo surgery and to achieve no gross residual disease with surgery (P = .002). Risk of death in NHB vs. NHW patients with UCS was 1.38 after adjustment for demographic factors and dropped after sequential adjustment for comorbidity score, neighborhood income, insurance status, stage and treatment by 4%, 16%, 7%, 19% and 10%, respectively, leaving 43.5% of the racial disparity in survival unexplained. In contrast, risk of death in NHBs vs. NHWs with OCS was 1.19 after adjustment for demographic factors and became insignificant after adjustment for comorbidity. Race was an independent prognostic factor in UCS but not in OCS.

CONCLUSIONS

Racial disparities exist in characteristics, treatment and survival in UCS and OCS with distinctions that merit additional research.

Jupiter microtubule-associated homolog 1 (JPT1): A predictive and pharmacodynamic biomarker of metformin response in endometrial cancers

Preoperative use of metformin in obese women with endometrioid endometrial cancer (EEC) reduces tumor proliferation and inhibits the mammalian target of rapamycin pathway, though is only effective in select cases. This study sought to identify a predictive and/or pharmacodynamic proteomic signature of metformin response to tailor its pharmacologic use. Matched pre‐ and post‐metformin‐treated tumor tissues from a recently completed preoperative window trial of metformin in EEC patients (ClinicalTrials.gov: NCT01911247) were analyzed by mass spectrometry (MS)‐based proteomic and immunohistochemical analyses. Jupiter microtubule‐associated homolog 1 (JPT1) was significantly elevated in metformin responders (n = 13) vs nonresponders (n = 7), and found to decrease in abundance in metformin responders following treatment; observations that were verified by immunohistochemical staining for JPT1. Metformin response and loss of JPT1 were assessed in RL95‐2 and ACI‐181 endometrial cancer (EC) cell lines. We further identified that silencing of JPT1 abundance does not alter cellular response to metformin or basal cell proliferation, but that JPT1 abundance does decrease in response to metformin treatment in RL95‐2 and ACI‐181 EC cell lines. These data suggest that JPT1 represents a predictive and pharmacodynamic biomarker of metformin response that, if validated in larger patient populations, may enable preoperative EEC patient stratification to metformin treatment and the ability to monitor patient response.

Efficient identification of neoantigen-specific T-cell responses in advanced human ovarian cancer

Background

Efficient identification of neoantigen-specific T-cell responses in epithelial ovarian cancer (EOC) remains a challenge. Existing investigations of spontaneous T-cell response to tumor neoepitope in EOC have taken the approach of comprehensive screening all neoantigen candidates, with a validation rate of 0.5–2%.

Methods

Whole-exome and transcriptome sequencing analysis of treatment-naive EOC patients were performed to identify neoantigen candidates, and the immunogenicity of prioritized neoantigens was evaluated by analyzing spontaneous neoantigen-specfic CD4⁺ and CD8⁺ T-cell responses in the tumor and/or peripheral blood. The biological relevance of neoantigen-specific T-cell lines and clones were analyzed by evaluating the capacity of autologous ovarian tumor recognition. Genetic transfer of T-cell receptor (TCR) from these neoantigen-specific T-cell clones into peripheral blood T-cells was conducted to generate neoepitope-specific T-cells. The molecular signature associated with positive neoantigen T-cell responses was investigated, and the impacts of expression level and lymphocyte source on neoantigen identification were explored.

Results

Using a small subset of prioritized neoantigen candidates, we were able to detect spontaneous CD4⁺ and/or CD8⁺ T-cell responses against neoepitopes from autologous lymphocytes in half of treatment-naïve EOC patients, with a significantly improved validation rate of 19%. Tumors from patients exhibiting neoantigen-specific T-cell responses exhibited a signature of upregulated antigen processing and presentation machinery, which was also associated with favorable patient survival in the TCGA ovarian cohort. T-cells specific against two mutated cancer-associated genes, NUP214 and JAK1, recognized autologous tumors. Gene-engineering with TCR from these neoantigen-specific T-cell clones conferred neoantigen-reactivity to peripheral T-cells.

Conclusions

Our study demonstrated the feasibility of efficiently identifying both CD4⁺ and CD8⁺ neoantigen-specific T-cells in EOC. Autologous lymphocytes genetically engineered with tumor antigen-specific TCR can be used to generate cells for use in the personalized adoptive T-cell transfer immunotherapy.

Electronic supplementary material

The online version of this article (10.1186/s40425-019-0629-6) contains supplementary material, which is available to authorized users.

Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences

Background

Although cell lines are an essential resource for studying cancer biology, many are of unknown ancestral origin, and their use may not be optimal for evaluating the biology of all patient populations.

Methods

An admixture analysis was performed using genome‐wide chip data from the Catalogue of Somatic Mutations in Cancer (COSMIC) Cell Lines Project to calculate genetic ancestry estimates for 1018 cancer cell lines. After stratifying the analyses by tissue and histology types, linear models were used to evaluate the influence of ancestry on gene expression and somatic mutation frequency.

Results

For the 701 cell lines with unreported ancestry, 215 were of East Asian origin, 30 were of African or African American origin, and 453 were of European origin. Notable imbalances were observed in ancestral representation across tissue type, with the majority of analyzed tissue types having few cell lines of African American ancestral origin, and with Hispanic and South Asian ancestry being almost entirely absent across all cell lines. In evaluating gene expression across these cell lines, expression levels of the genes neurobeachin line 1 (NBEAL1), solute carrier family 6 member 19 (SLC6A19), HEAT repeat containing 6 (HEATR6), and epithelial cell transforming 2 like (ECT2L) were associated with ancestry. Significant differences were also observed in the proportions of somatic mutation types across cell lines with varying ancestral proportions.

Conclusions

By estimating genetic ancestry for 1018 cancer cell lines, the authors have produced a resource that cancer researchers can use to ensure that their cell lines are ancestrally representative of the populations they intend to affect. Furthermore, the novel ancestry‐specific signal identified underscores the importance of ancestral awareness when studying cancer.

Preclinical cancer cell line research is often conducted without an awareness of ancestral background, which results in incongruities between the genetic backgrounds of used cell lines and the patient populations they are intended to represent. By calculating genetic ancestry for 1018 common cancer cell lines and identifying ancestry‐specific expression and somatic mutation patterns, the importance of ancestral awareness is emphasized, and a resource is provided that can be used by cancer researchers to ensure that their cell lines are ancestrally representative of the populations they aim to impact.

PINK1 Interacts with VCP/p97 and Activates PKA to Promote NSFL1C/p47 Phosphorylation and Dendritic Arborization in Neurons

While PTEN-induced kinase 1 (PINK1) is well characterized for its role in mitochondrial homeostasis, much less is known concerning its ability to prevent synaptodendritic degeneration. Using unbiased proteomic methods, we identified valosin-containing protein (VCP) as a major PINK1-interacting protein. RNAi studies demonstrate that both VCP and its cofactor NSFL1C/p47 are necessary for the ability of PINK1 to increase dendritic complexity. Moreover, PINK1 regulates phosphorylation of p47, but not the VCP co-factor UFD1. Although neither VCP nor p47 interact directly with PKA, we found that PINK1 binds and phosphorylates the catalytic subunit of PKA at T197 [PKAcat(pT197)], a site known to activate the PKA holoenzyme. PKA in turn phosphorylates p47 at a novel site (S176) to regulate dendritic complexity. Given that PINK1 physically interacts with both the PKA holoenzyme and the VCP-p47 complex to promote dendritic arborization, we propose that PINK1 scaffolds a novel PINK1-VCP-PKA-p47 signaling pathway to orchestrate dendritogenesis in neurons. These findings highlight an important mechanism by which proteins genetically implicated in Parkinson's disease (PD; PINK1) and frontotemporal dementia (FTD; VCP) interact to support the health and maintenance of neuronal arbors.

Recent advances and opportunities in proteomic analyses of tumour heterogeneity

Solid tumour malignancies comprise a highly variable admixture of tumour and non-tumour cellular populations, forming a complex cellular ecosystem and tumour microenvironment. This tumour heterogeneity is not incidental, and is known to correlate with poor patient prognosis for many cancer types. Indeed, non-malignant cell populations, such as vascular endothelial and immune cells, are known to play key roles supporting and, in some cases, driving aggressive tumour biology, and represent targets of emerging therapeutics, such as antiangiogenesis and immune checkpoint inhibitors. The biochemical interplay between these cellular populations and how they contribute to molecular tumour heterogeneity remains enigmatic, particularly from the perspective of the tumour proteome. This review focuses on recent advances in proteomic methods, namely imaging mass spectrometry, single-cell proteomic techniques, and preanalytical sample processing, that are uniquely positioned to enable detailed analysis of discrete cellular populations within tumours to improve our understanding of tumour proteomic heterogeneity. This review further emphasizes the opportunity afforded by the application of these techniques to the analysis of tumour heterogeneity in formalin-fixed paraffin-embedded archival tumour tissues, as these represent an invaluable resource for retrospective analyses that is now routinely accessible, owing to recent technological and methodological advances in tumour tissue proteomics. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Race-specific molecular alterations correlate with differential outcomes for black and white endometrioid endometrial cancer patients

BACKGROUND

The objective of this study was to identify molecular alterations associated with disease outcomes for white and black patients with endometrioid endometrial cancer (EEC).

METHODS

EEC samples from black (n = 17) and white patients (n = 13) were analyzed by proteomics (liquid chromatography-tandem mass spectrometry) and transcriptomics (RNA-seq). Coordinate alterations were validated with RNA-seq data from black (n = 49) and white patients (n = 216). Concordantly altered candidates were further tested for associations with race-specific progression-free survival (PFS) in black (n = 64) or white patients (n = 267) via univariate and multivariate Cox regression modeling and log-rank testing.

RESULTS

Discovery analyses revealed significantly altered candidate proteins and transcripts between black and white patients, suggesting modulation of tumor cell viability in black patients and cell death signaling in black and white patients. Eighty-nine candidates were validated as altered between these patient cohorts, and a subset significantly correlated with differential PFS. White-specific PFS candidates included serpin family A member 4 (SERPINA4; hazard ratio [HR], 0.89; Wald P value = .02), integrin subunit α3 (ITGA3; HR, 0.76; P = .03), and Bet1 Golgi vesicular membrane trafficking protein like (BET1L; HR, 0.48; P = .04). Black-specific PFS candidates included family with sequence similarity 228 member B (FAM228B; HR, 0.13; P = .001) and HEAT repeat containing 6 (HEATR6; HR, 4.94; P = .047). Several candidates were also associated with overall survival (SERPINA4 and ITGA3) as well as PFS independent of disease stage, grade and myometrial invasion (SERPINA4, BET1L and FAM228B).

CONCLUSIONS

This study has identified and validated molecular alterations in tumors from black and white EEC patients, including candidates significantly associated with altered disease outcomes within these patient cohorts. Cancer 2017;123:4004-12. © 2017 American Cancer Society.

Impact of age at diagnosis on racial disparities in endometrial cancer patients

INTRODUCTION

Although black patients with endometrial cancer (EC) have worse survival compared with white patients, the interaction between age/race has not been examined. The primary objective was to evaluate the impact of age at diagnosis on racial disparities in disease presentation and outcome in EC.

METHODS

We evaluated women diagnosed with EC between 1991 and 2010 from the Surveillance, Epidemiology, and End Results. Mutation status for TP53 or PTEN, or with the aggressive integrative, transcript-based, or somatic copy number alteration-based molecular subtype were acquired from the Cancer Genome Atlas. Logistic regression model was used to estimate the interaction between age and race on histology. Cox regression model was used to estimate the interaction between age and race on survival.

RESULTS

78,184 white and 8518 black patients with EC were analyzed. Median age at diagnosis was 3-years younger for black vs. white patients with serous cancer and carcinosarcoma (P<0.0001). The increased presentation of non-endometrioid histology with age was larger in black vs. white patients (P<0.0001). The racial disparity in survival and cancer-related mortality was more prevalent in black vs. white patients, and in younger vs. older patients (P<0.0001). Mutations in TP53, PTEN and the three aggressive molecular subtypes each varied by race, age and histology.

CONCLUSIONS

Aggressive histology and molecular features were more common in black patients and older age, with greater impact of age on poor tumor characteristics in black vs. white patients. Racial disparities in outcome were larger in younger patients. Intervention at early ages may mitigate racial disparities in EC.

Abstract 5277: Proteome and transcriptome alterations in black endometrial cancer patients correlate with poor disease outcome

Objective: Black endometrial cancer patients are more than twice as likely to die from their disease as White patients. This study sought to identify alterations in the proteome and transcriptome of primary tumor tissues from White and Black endometrioid endometrial cancer (EEC) patients associated with differential outcome.

Methods: An integrated proteomic and transcriptomic analysis (LC-MS/MS and RNA-seq) was performed on White (n=13) and Black (n=17) EEC patient tissues. Significant and concordantly altered protein and transcript candidates were validated against publicly available RNA-seq data (TCGA UCEC) from White (n=216) and Black (n=49) EEC patients. Validated candidates were further correlated with overall (OS, n=356 White and Black patients) and progression-free survival (PFS, n=331 White and Black patients) to identify candidates significantly associated with differential disease outcome. Alterations of outcome-associated candidates were validated in an independent cohort of White (n=115) and Black (n=17) EEC patient transcript expression data.

Results: We identified and validated 89 proteins and transcripts significantly altered between White vs Black EEC patients. Pathway analyses revealed candidates elevated in White EEC patients correlated with marked activation of molecular signaling pathways regulating viral infection, but inhibition of those regulating cell death and necrosis. Candidates elevated in Black EEC patients largely correlated with activation of cell viability and nucleic acid metabolism, but inhibition of cell death, glucose metabolism disorder and inflammatory signaling. Correlation with patient outcome measures revealed 11 candidates significantly associated with differential OS and 8 candidates with differential PFS in EEC patients. All outcome-associated candidates elevated in White patients significantly correlated with a low risk of poor OS and poor PFS (Hazard Ratio (HR) &lt; 1, Wald p-value &lt; 0.05). Conversely, the majority of outcome-associated candidates (88%) elevated in Black patients correlated with a high risk of poor OS and poor PFS (HR &gt; 1, Wald p-value &lt; 0.05). Several OS (27%) and PFS (75%) candidates remained significant after adjustment for disease stage and grade as well as myometrial invasion. Alteration trends for several OS (27%) and PFS (25%) candidates were validated in an independent cohort of White and Black EEC patients.

Conclusions: Our analyses identified and confirmed molecular alterations between White and Black EEC patients, including outcome-associated candidates largely supportive of better outcome in White patients, but poor outcome in Black patients. These findings define molecular alterations in White and Black EEC patients consistent with the historic disparity of poor outcome for Black patients warranting further investigation of these candidates in Black EEC disease pathology.

Citation Format: Nicholas W. Bateman, Elizabeth Dubil, Guisong Wang, Brian L. Hood, Tracy Litzi, Julie Oliver, Kathleen M. Darcy, Chad A. Hamilton, Thomas P. Conrads, George L. Maxwell. Proteome and transcriptome alterations in black endometrial cancer patients correlate with poor disease outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5277. doi:10.1158/1538-7445.AM2017-5277

Establishment and characterization of a platinum- and paclitaxel-resistant high grade serous ovarian carcinoma cell line

High grade serous ovarian cancer (HGSOC) patients have a high recurrence rate after surgery and adjuvant chemotherapy due to inherent or acquired drug resistance. Cell lines derived from HGSOC tumors that are resistant to chemotherapeutic agents represent useful pre-clinical models for drug discovery. Here, we describe establishment of a human ovarian carcinoma cell line, which we term WHIRC01, from a patient-derived mouse xenograft established from a chemorefractory HGSOC patient who did not respond to carboplatin and paclitaxel therapy. This newly derived cell line is platinum- and paclitaxel-resistant with cisplatin, carboplatin, and paclitaxel half-maximal lethal doses of 15, 130, and 20 µM, respectively. Molecular characterization of this cell line was performed using targeted DNA exome sequencing, transcriptomics (RNA-seq), and mass spectrometry-based proteomic analyses. Results from exomic sequencing revealed mutations in TP53 consistent with HGSOC. Transcriptomic and proteomic analyses of WHIRC01 showed high level of alpha-enolase and vimentin, which are associated with cell migration and epithelial-mesenchymal transition. WHIRC01 represents a chemorefractory human HGSOC cell line model with a comprehensive molecular profile to aid future investigations of drug resistance mechanisms and screening of chemotherapeutic agents.