H2Bub1 loss is an early contributor to clear cell ovarian cancer progression

Epigenetic aberrations, including posttranslational modifications of core histones, are major contributors to cancer. Here, we define the status of histone H2B monoubiquitylation (H2Bub1) in clear cell ovarian carcinoma (CCOC), low-grade serous carcinoma, and endometrioid carcinomas. We report that clear cell carcinomas exhibited profound loss, with nearly all cases showing low or negative H2Bub1 expression. Moreover, we found that H2Bub1 loss occurred in endometriosis and atypical endometriosis, which are established precursors to CCOCs. To examine whether dysregulation of a specific E3 ligase contributes to the loss of H2Bub1, we explored expression of ring finger protein 40 (RNF40), ARID1A, and UBR7 in the same case cohort. Loss of RNF40 was significantly and profoundly correlated with loss of H2Bub1. Using genome-wide DNA methylation profiles of 230 patients with CCOC, we identified hypermethylation of RNF40 in CCOC as a likely mechanism underlying the loss of H2Bub1. Finally, we demonstrated that H2Bub1 depletion promoted cell proliferation and clonogenicity in an endometriosis cell line. Collectively, our results indicate that H2Bub1 plays a tumor-suppressive role in CCOCs and that its loss contributes to disease progression.

A perception-based nanosensor platform to detect cancer biomarkers

Conventional molecular recognition elements, such as antibodies, present issues for developing biomolecular assays for use in certain technologies, such as implantable devices. Additionally, antibody development and use, especially for highly multiplexed applications, can be slow and costly. We developed a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids. We demonstrated this platform in gynecologic cancers, often diagnosed at advanced stages, leading to low survival rates. We investigated the detection of protein biomarkers in uterine lavage samples, which are enriched with certain cancer markers compared to blood. We found that the method enables the simultaneous detection of multiple biomarkers in patient samples, with F1-scores of ~0.95 in uterine lavage samples from patients with cancer. This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements.

En route to single-step, two-phase purification of carbon nanotubes facilitated by high-throughput spectroscopy

Chirality purification of single-walled carbon nanotubes (SWCNTs) is desirable for applications in many fields, but general utility is currently hampered by low throughput. We discovered a method to obtain single-chirality SWCNT enrichment by the aqueous two-phase extraction (ATPE) method in a single step. To achieve appropriate resolution, a biphasic system of non-ionic tri-block copolymer surfactant is varied with an ionic surfactant. A nearly-monochiral fraction of SWCNTs can then be harvested from the top phase. We also found, via high-throughput, near-infrared excitation-emission photoluminescence spectroscopy, that the parameter space of ATPE can be mapped to probe the mechanics of the separation process. Finally, we found that optimized conditions can be used for sorting of SWCNTs wrapped with ssDNA as well. Elimination of the need for surfactant exchange and simplicity of the separation process make the approach promising for high-yield generation of purified single-chirality SWCNT preparations.

Leveraging locus-specific epigenetic heterogeneity to improve the performance of blood-based DNA methylation biomarkers

BACKGROUND

Variation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass ) that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification.

RESULTS

We developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-ml) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers.

CONCLUSIONS

Our results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitates the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically diverse ovarian carcinomas, indicating broad utility of ZNF154 for use as a biomarker of ovarian cancer.

Noninvasive ovarian cancer biomarker detection via an optical nanosensor implant

Patients with high-grade serous ovarian carcinoma (HGSC) exhibit poor 5-year survival rates, which may be significantly improved by early-stage detection. The U.S. Food and Drug Administration-approved biomarkers for HGSC-CA-125 (cancer antigen 125) and HE4 (human epididymis protein 4)-do not generally appear at detectable levels in the serum until advanced stages of the disease. An implantable device placed proximal to disease sites, such as in or near the fallopian tube, ovary, uterine cavity, or peritoneal cavity, may constitute a feasible strategy to improve detection of HGSC. We engineered a prototype optical sensor composed of an antibody-functionalized carbon nanotube complex, which responds quantitatively to HE4 via modulation of the nanotube optical bandgap. The complexes measured HE4 with nanomolar sensitivity to differentiate disease from benign patient biofluids. The sensors were implanted into four models of ovarian cancer, within a semipermeable membrane, enabling the optical detection of HE4 within the live animals. We present the first in vivo optical nanosensor capable of noninvasive cancer biomarker detection in orthotopic models of disease.

Characterization of the first fully human anti-TEM1 scFv in models of solid tumor imaging and immunotoxin-based therapy

Tumor endothelial marker 1 (TEM1) has been identified as a novel surface marker upregulated on the blood vessels and stroma in many solid tumors. We previously isolated a novel single-chain variable fragment (scFv) 78 against TEM1 from a yeast display scFv library. Here, we evaluated the potential applications of scFv78 as a tool for tumor molecular imaging, immunotoxin-based therapy and nanotherapy. Epitope mapping, three-dimensional structure docking and affinity measurements indicated that scFv78 could bind to both human and murine TEM1, with equivalent affinity, at a well-conserved conformational epitope. The rapid internalization of scFv78 and scFv78-labeled nanoparticles was triggered after specific TEM1 binding. The scFv78-saporin immunoconjugate also exerted dose-dependent cytotoxicity with high specificity to TEM1-positive cells in vitro. Finally, specific and sensitive tumor localization of scFv78 was confirmed with optical imaging in a tumor mouse model that has highly endogenous mTEM1 expression in the vasculature. Our data indicated that scFv78, the first fully human anti-TEM1 recombinant antibody, recognizes both human and mouse TEM1 and has unique and favorable features that are advantageous for the development of imaging probes or antibody-toxin conjugates for a large spectrum of human TEM1-positive solid tumors.