Genome-wide repeat landscapes in cancer and cell-free DNA.

Genetic changes in repetitive sequences are a hallmark of cancer and other diseases, but characterizing these has been challenging using standard sequencing approaches. We developed a de novo kmer finding approach, called ARTEMIS (Analysis of RepeaT EleMents in dISease), to identify repeat elements from whole-genome sequencing. Using this method, we analyzed 1.2 billion kmers in 2837 tissue and plasma samples from 1975 patients, including those with lung, breast, colorectal, ovarian, liver, gastric, head and neck, bladder, cervical, thyroid, or prostate cancer. We identified tumor-specific changes in these patients in 1280 repeat element types from the LINE, SINE, LTR, transposable element, and human satellite families. These included changes to known repeats and 820 elements that were not previously known to be altered in human cancer. Repeat elements were enriched in regions of driver genes, and their representation was altered by structural changes and epigenetic states. Machine learning analyses of genome-wide repeat landscapes and fragmentation profiles in cfDNA detected patients with early-stage lung or liver cancer in cross-validated and externally validated cohorts. In addition, these repeat landscapes could be used to noninvasively identify the tissue of origin of tumors. These analyses reveal widespread changes in repeat landscapes of human cancers and provide an approach for their detection and characterization that could benefit early detection and disease monitoring of patients with cancer.

Cell-free DNA approaches for cancer early detection and interception.

Rapid advancements in the area of early cancer detection have brought us closer to achieving the goals of finding cancer early enough to treat or cure it, while avoiding harms of overdiagnosis. We evaluate progress in the development of early cancer detection tests in the context of the current principles for cancer screening. We review cell-free DNA (cfDNA)-based approaches using mutations, methylation, or fragmentomes for early cancer detection. Lastly, we discuss the challenges in demonstrating clinical utility of these tests before integration into routine clinical care.

Inaugurating High-Throughput Profiling of Extracellular Vesicles for Earlier Ovarian Cancer Detection.

Detecting early cancer through liquid biopsy is challenging due to the lack of specific biomarkers for early lesions and potentially low levels of these markers. The current study systematically develops an extracellular-vesicle (EV)-based test for early detection, specifically focusing on high-grade serous ovarian carcinoma (HGSOC). The marker selection is based on emerging insights into HGSOC pathogenesis, notably that it arises from precursor lesions within the fallopian tube. This work thus establishes murine fallopian tube (mFT) cells with oncogenic mutations and performs proteomic analyses on mFT-derived EVs. The identified markers are then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood of tumor-bearing mice, mFT-EV markers increase with tumor initiation, supporting their potential use in early cancer detection. A pilot clinical study (n = 51) further narrows EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. The combined expression of these markers distinguishes HGSOC from non-cancer with 89% sensitivity and 93% specificity. The same markers are also effective in classifying three groups (non-cancer, early-stage HGSOC, and late-stage HGSOC). The developed approach, for the first time inaugurated in fallopian tube-derived EVs, could be a minimally invasive tool to monitor women at high risk of ovarian cancer for timely intervention.

Single-molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer.

Somatic mutations are a hallmark of tumorigenesis and may be useful for non-invasive diagnosis of cancer. We analyzed whole-genome sequencing data from 2,511 individuals in the Pan-Cancer Analysis of Whole Genomes (PCAWG) study as well as 489 individuals from four prospective cohorts and found distinct regional mutation type-specific frequencies in tissue and cell-free DNA from patients with cancer that were associated with replication timing and other chromatin features. A machine-learning model using genome-wide mutational profiles combined with other features and followed by CT imaging detected >90% of patients with lung cancer, including those with stage I and II disease. The fixed model was validated in an independent cohort, detected patients with cancer earlier than standard approaches and could be used to monitor response to therapy. This approach lays the groundwork for non-invasive cancer detection using genome-wide mutation features that may facilitate cancer screening and monitoring.

Cell-Free DNA Fragmentomes in the Diagnostic Evaluation of Patients With Symptoms Suggestive of Lung Cancer.

BACKGROUND: The diagnostic workup of individuals suspected of having lung cancer can be complex and protracted because conventional symptoms of lung cancer have low specificity and sensitivity. RESEARCH QUESTION: Among individuals with symptoms of lung cancer, can a blood-based approach to analyze cell-free DNA (cfDNA) fragmentation (the DNA evaluation of fragments for early interception [DELFI] score) enhance evaluation for the possible presence of lung cancer? STUDY DESIGN AND METHODS: Adults were referred to Bispebjerg Hospital (Copenhagen, Denmark) for diagnostic evaluation of initial imaging anomalies and symptoms consistent with lung cancer. Numbers and types of symptoms were extracted from medical records. cfDNA from plasma samples obtained at the prediagnostic visit was isolated, sequenced, and analyzed for genome-wide cfDNA fragmentation patterns. The relationships among clinical presentation, cancer status, and DELFI score were examined. RESULTS: A total of 296 individuals were analyzed. Median DELFI scores were higher for those with lung cancer (n = 98) than those without cancer (n = 198; 0.94 vs 0.19; P < .001). In a multivariate model adjusted for age, smoking history, and presenting symptoms, the addition of the DELFI score improved the prediction of lung cancer for those who demonstrated symptoms (area under the receiver operating characteristic curve, 0.74-0.94). INTERPRETATION: The DELFI score distinguishes individuals with lung cancer from those without cancer better than suspicious symptoms do. These results represent proof-of-concept support that fragmentation-based biomarker approaches may facilitate diagnostic resolution for patients with concerning symptoms of lung cancer.

Profiling extracellular vesicles in circulation enables the early detection of ovarian cancer.

Ovarian cancer is a heterogeneous group of tumors in both cell type and natural history. While outcomes are generally favorable when detected early, the most common subtype, high-grade serous carcinoma (HGSOC), typically presents at an advanced stage and portends less favorable prognoses. Its aggressive nature has thwarted early detection efforts through conventional detection methods such as serum CA125 and ultrasound screening and thus inspired the investigation of novel biomarkers. Here, we report the systematic development of an extracellular-vesicle (EV)-based test to detect early-stage HGSOC. Our study is based on emerging insights into HGSOC biology, notably that it arises from precursor lesions within the fallopian tube before traveling to ovarian and/or peritoneal surfaces. To identify HGSOC marker candidates, we established murine fallopian tube (mFT) cells with oncogenic mutations in Brca1/2, Tp53 , and Pten genes, and performed proteomic analyses on mFT EVs. The identified markers were then evaluated with an orthotopic HGSOC animal model. In serially-drawn blood samples of tumor-bearing mice, mFT-EV markers increased with tumor initiation, supporting their potential use in early cancer detection. A pilot human clinical study ( n = 51) further narrowed EV markers to five candidates, EpCAM, CD24, VCAN, HE4, and TNC. Combined expression of these markers achieved high OvCa diagnostic accuracy (cancer vs. non-cancer) with a sensitivity of 0.89 and specificity of 0.93. The same five markers were also effective in a three-group classification: non-cancer, early-stage (I & II) HGSOC, and late-stage (III & IV) HGSOC. In particular, they differentiated early-stage HGSOC from the rest with a specificity of 0.91. Minimally invasive and repeatable, this EV-based testing could be a versatile and serial tool for informing patient care and monitoring women at high risk for ovarian cancer.

Metastatic Colorectal Cancer Treatment Response Evaluation by Ultra-Deep Sequencing of Cell-Free DNA and Matched White Blood Cells.

PURPOSE: Circulating tumor DNA (ctDNA) has the potential to guide therapy selection and monitor treatment response in patients with metastatic cancer. However, germline and clonal hematopoiesis-associated alterations can confound identification of tumor-specific mutations in cell-free DNA (cfDNA), often requiring additional sequencing of tumor tissue. The current study assessed whether ctDNA-based treatment response monitoring could be performed in a tumor tissue-independent manner by combining ultra-deep targeted sequencing analyses of cfDNA with patient-matched white blood cell (WBC)-derived DNA. EXPERIMENTAL DESIGN: In total, 183 cfDNA and 49 WBC samples, along with 28 tissue samples, from 52 patients with metastatic colorectal cancer participating in the prospective phase III CAIRO5 clinical trial were analyzed using an ultra-deep targeted sequencing liquid biopsy assay. RESULTS: The combined cfDNA and WBC analysis prevented false-positives due to germline or hematopoietic variants in 40% of patients. Patient-matched tumor tissue sequencing did not provide additional information. Longitudinal analyses of ctDNA were more predictive of overall survival than standard-of-care radiological response evaluation. ctDNA mutations related to primary or acquired resistance to panitumumab were identified in 42% of patients. CONCLUSIONS: Accurate calling of ctDNA mutations for treatment response monitoring is feasible in a tumor tissue-independent manner by combined cfDNA and patient-matched WBC genomic DNA analysis. This tissue biopsy-independent approach simplifies sample logistics and facilitates the application of liquid biopsy ctDNA testing for evaluation of emerging therapy resistance, opening new avenues for early adaptation of treatment regimens.

Detecting Liver Cancer Using Cell-Free DNA Fragmentomes.

Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection. SIGNIFICANCE: There is a great need for accessible and sensitive screening approaches for HCC worldwide. We have developed an approach for examining genome-wide cfDNA fragmentation features to provide a high-performing and cost-effective approach for liver cancer detection. See related commentary Rolfo and Russo, p. 532. This article is highlighted in the In This Issue feature, p. 517.

Translating the evolving molecular landscape of tumors to biomarkers of response for cancer immunotherapy.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapeutics, triggering studies to understand the molecular and cellular wiring of response and resistance. Our increased understanding of the underlying biology of response to ICI has enabled the investigation of tumor-intrinsic and -extrinsic features that may predict therapeutic outcomes. In parallel, liquid biopsy measurements of circulating tumor DNA (ctDNA) can be used to assess real-time molecular responses and guide clinical decisions during ICI. The combination of these approaches provides a deeper understanding of cancer biology, immunoediting, and evolution during ICI and promise to extend the utility of immunotherapies for patients with cancer.

KRAS A146 Mutations Are Associated With Distinct Clinical Behavior in Patients With Colorectal Liver Metastases.

Somatic KRAS mutations occur in approximately half of the patients with metastatic colorectal cancer (mCRC). Biologic tumor characteristics differ on the basis of the KRAS mutation variant. KRAS mutations are known to influence patient prognosis and are used as predictive biomarker for treatment decisions. This study examined clinical features of patients with mCRC with a somatic mutation in KRAS G12, G13, Q61, K117, or A146. METHODS: A total of 419 patients with colorectal cancer with initially unresectable liver-limited metastases, who participated in a multicenter prospective trial, were evaluated for tumor tissue KRAS mutation status. For the subgroup of patients who carried a KRAS mutation and were treated with bevacizumab and doublet or triplet chemotherapy (N = 156), pretreatment circulating tumor DNA levels were analyzed, and total tumor volume (TTV) was quantified on the pretreatment computed tomography images. RESULTS: Most patients carried a KRAS G12 mutation (N = 112), followed by mutations in G13 (N = 15), A146 (N = 12), Q61 (N = 9), and K117 (N = 5). High plasma circulating tumor DNA levels were observed for patients carrying a KRAS A146 mutation versus those with a KRAS G12 mutation, with median mutant allele frequencies of 48% versus 19%, respectively. Radiologic TTV revealed this difference to be associated with a higher tumor load in patients harboring a KRAS A146 mutation (median TTV 672 cm3 [A146] v 74 cm3 [G12], P = .036). Moreover, KRAS A146 mutation carriers showed inferior overall survival compared with patients with mutations in KRAS G12 (median 10.7 v 26.4 months; hazard ratio = 2.5; P = .003). CONCLUSION: Patients with mCRC with a KRAS A146 mutation represent a distinct molecular subgroup of patients with higher tumor burden and worse clinical outcomes, who might benefit from more intensive treatments. These results highlight the importance of testing colorectal cancer for all KRAS mutations in routine clinical care.

Detection and characterization of lung cancer using cell-free DNA fragmentomes.

Non-invasive approaches for cell-free DNA (cfDNA) assessment provide an opportunity for cancer detection and intervention. Here, we use a machine learning model for detecting tumor-derived cfDNA through genome-wide analyses of cfDNA fragmentation in a prospective study of 365 individuals at risk for lung cancer. We validate the cancer detection model using an independent cohort of 385 non-cancer individuals and 46 lung cancer patients. Combining fragmentation features, clinical risk factors, and CEA levels, followed by CT imaging, detected 94% of patients with cancer across stages and subtypes, including 91% of stage I/II and 96% of stage III/IV, at 80% specificity. Genome-wide fragmentation profiles across ~13,000 ASCL1 transcription factor binding sites distinguished individuals with small cell lung cancer from those with non-small cell lung cancer with high accuracy (AUC = 0.98). A higher fragmentation score represented an independent prognostic indicator of survival. This approach provides a facile avenue for non-invasive detection of lung cancer.

White blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer.

Liquid biopsies are providing new opportunities for detection of residual disease in cell-free DNA (cfDNA) after surgery but may be confounded through identification of alterations arising from clonal hematopoiesis. Here, we identify circulating tumor-derived DNA (ctDNA) alterations through ultrasensitive targeted sequencing analyses of matched cfDNA and white blood cells from the same patient. We apply this approach to analyze samples from patients in the CRITICS trial, a phase III randomized controlled study of perioperative treatment in patients with operable gastric cancer. After filtering alterations from matched white blood cells, the presence of ctDNA predicts recurrence when analyzed within nine weeks after preoperative treatment and after surgery in patients eligible for multimodal treatment. These analyses provide a facile method for distinguishing ctDNA from other cfDNA alterations and highlight the utility of ctDNA as a predictive biomarker of patient outcome to perioperative cancer therapy and surgical resection in patients with gastric cancer.

Genome-wide cell-free DNA fragmentation in patients with cancer.

Cell-free DNA in the blood provides a non-invasive diagnostic avenue for patients with cancer1. However, characteristics of the origins and molecular features of cell-free DNA are poorly understood. Here we developed an approach to evaluate fragmentation patterns of cell-free DNA across the genome, and found that profiles of healthy individuals reflected nucleosomal patterns of white blood cells, whereas patients with cancer had altered fragmentation profiles. We used this method to analyse the fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric or bile duct cancer and 245 healthy individuals. A machine learning model that incorporated genome-wide fragmentation features had sensitivities of detection ranging from 57% to more than 99% among the seven cancer types at 98% specificity, with an overall area under the curve value of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation-based cell-free DNA analyses detected 91% of patients with cancer. The results of these analyses highlight important properties of cell-free DNA and provide a proof-of-principle approach for the screening, early detection and monitoring of human cancer.

Nanoformulation of Talazoparib Delays Tumor Progression and Ascites Formation in a Late Stage Cancer Model.

Talazoparib, a potent PARP inhibitor, induces synthetic lethality in BRCA-deficient cancers making it an attractive candidate for ovarian cancer treatment. However, its potency lends itself to side effects associated more closely with traditional chemotherapeutics than other clinically approved PARP inhbitors. We sought to formulate Talazoparib in a nanoparticle delivery system, which allows the drug to be administered intraperitoneally. This was done to specifically target peritoneal dissemination of late stage metastatic ovarian cancer and increase talazoparib's therapeutic efficacy while minimizing toxic side effects. NanoTalazoparib was developed and characterized with regard to its size, loading, and surface charge. Talazoparib and NanoTalazoparib were tested on a panel of murine and human BRCA cell lines and the dose response was compared to Olaparib's, the currently used PARP inhibitor. Therapeutic efficacy was tested in vivo in a Brca peritoneal cancer model that mimics late stage disseminated disease. NanoTalazoparib has a diameter of about 70 nm with a neutral surface charge and ~75% encapsulation efficiency, which slowly releases the drug over several hours. Dose response analysis indicated that the murine cell lines with conditional BRCA1/2, PTEN, and TP53 deletions had the lowest IC50s. NanoTalazoparib administered on a schedule of three doses weekly slowed disease progression and resulted in significantly less mice with ascites at the end point compared to controls. These results indicate that the slow release nanoformulation, NanoTalazoparib, effectively delivers PARP inhibitor therapy to the peritoneal cavity for disseminated cancer treatment. The ability to decrease ascites formation with the introduction of intraperitoneal NanoTalazoparib suggests this treatment may be an effective way to treat ovarian cancer-associated ascites and slow disease progression.

Unraveling the Cellular Mechanism of Assembling Cholesterols for Selective Cancer Cell Death.

Acquired drug resistance remains a challenge in chemotherapy. Here we show enzymatic, in situ assembling of cholesterol derivatives to act as polypharmaceuticals for selectively inducing death of cancer cells via multiple pathways and without inducing acquired drug resistance. A conjugate of tyrosine and cholesterol (TC), formed by enzyme-catalyzed dephosphorylation of phosphorylate TC, self-assembles selectively on or in cancer cells. Acting as polypharmaceuticals, the assemblies of TC augment lipid rafts, aggregate extrinsic cell death receptors (e.g., DR5, CD95, or TRAILR), modulate the expression of oncoproteins (e.g., Src and Akt), disrupt the dynamics of cytoskeletons (e.g., actin filaments or microtubules), induce endoplasmic reticulum stress, and increase the production of reactive oxygen species, thus resulting in cell death and preventing acquired drug resistance. Moreover, the assemblies inhibit the growth of platinum-resistant ovarian cancer tumor in a murine model. This work illustrates the use of instructed assembly (iA) in cellular environment to form polypharmaceuticals in situ that not only interact with multiple proteins, but also modulate membrane dynamics for developing novel anticancer therapeutics. IMPLICATIONS: As a multifaceted strategy for controlling cancer cell death, iA minimized acquired resistance of cancer cells, which is a new strategy to amplify the genetic difference between cancer and normal cells and provides a promise for overcoming drug resistance in cancer therapy.Visual Overview: http://mcr.aacrjournals.org/content/molcanres/17/4/907/F1.large.jpg.

Early Noninvasive Detection of Response to Targeted Therapy in Non-Small Cell Lung Cancer.

With the advent of precision oncology, there is an urgent need to develop improved methods for rapidly detecting responses to targeted therapies. Here, we have developed an ultrasensitive measure of cell-free tumor load using targeted and whole-genome sequencing approaches to assess responses to tyrosine kinase inhibitors in patients with advanced lung cancer. Analyses of 28 patients treated with anti-EGFR or HER2 therapies revealed a bimodal distribution of cell-free circulating tumor DNA (ctDNA) after therapy initiation, with molecular responders having nearly complete elimination of ctDNA (>98%). Molecular nonresponders displayed limited changes in ctDNA levels posttreatment and experienced significantly shorter progression-free survival (median 1.6 vs. 13.7 months, P < 0.0001; HR = 66.6; 95% confidence interval, 13.0-341.7), which was detected on average 4 weeks earlier than CT imaging. ctDNA analyses of patients with radiographic stable or nonmeasurable disease improved prediction of clinical outcome compared with CT imaging. These analyses provide a rapid approach for evaluating therapeutic response to targeted therapies and have important implications for the management of patients with cancer and the development of new therapeutics.Significance: Cell-free tumor load provides a novel approach for evaluating longitudinal changes in ctDNA during systemic treatment with tyrosine kinase inhibitors and serves an unmet clinical need for real-time, noninvasive detection of tumor response to targeted therapies before radiographic assessment.See related commentary by Zou and Meyerson, p. 1038.

Epigenetic Reprogramming Strategies to Reverse Global Loss of 5-Hydroxymethylcytosine, a Prognostic Factor for Poor Survival in High-grade Serous Ovarian Cancer.

Purpose: A major challenge in platinum-based cancer therapy is the clinical management of chemoresistant tumors, which have a largely unknown pathogenesis at the level of epigenetic regulation.Experimental Design: We evaluated the potential of using global loss of 5-hydroxymethylcytosine (5-hmC) levels as a novel diagnostic and prognostic epigenetic marker to better assess platinum-based chemotherapy response and clinical outcome in high-grade serous tumors (HGSOC), the most common and deadliest subtype of ovarian cancer. Furthermore, we identified a targetable pathway to reverse these epigenetic changes, both genetically and pharmacologically.Results: This study shows that decreased 5-hmC levels are an epigenetic hallmark for malignancy and tumor progression in HGSOC. In addition, global 5-hmC loss is associated with a decreased response to platinum-based chemotherapy, shorter time to relapse, and poor overall survival in patients newly diagnosed with HGSOC. Interestingly, the rescue of 5-hmC loss restores sensitivity to platinum chemotherapy in vitro and in vivo, decreases the percentage of tumor cells with cancer stem cell markers, and increases overall survival in an aggressive animal model of platinum-resistant disease.Conclusions: Consequently, a global analysis of patient 5-hmC levels should be included in future clinical trials, which use pretreatment with epigenetic adjuvants to elevate 5-hmC levels and improve the efficacy of current chemotherapies. Identifying prognostic epigenetic markers and altering chemotherapeutic regimens to incorporate DNMTi pretreatment in tumors with low 5-hmC levels could have important clinical implications for newly diagnosed HGSOC disease. Clin Cancer Res; 24(6); 1389-401. ©2017 AACR.

Selectively Inducing Cancer Cell Death by Intracellular Enzyme-Instructed Self-Assembly (EISA) of Dipeptide Derivatives.

Tight ligand-receptor binding, paradoxically, is a major root of drug resistance in cancer chemotherapy. To address this problem, instead of using conventional inhibitors or ligands, this paper focuses on the development of a novel process-enzyme-instructed self-assembly (EISA)-to kill cancer cells selectively. Here it is demonstrated that EISA as an intracellular process to generate nanofibrils of short peptides for selectively inhibiting cancer cell proliferation, including drug resistant ones. As the process that turns the non-self-assembling precursors into the self-assembling peptides upon the catalysis of carboxylesterases (CES), EISA occurs intracellularly to selectively inhibit a range of cancer cells that exhibit relatively high CES activities. More importantly, EISA inhibits drug resistant cancer cells (e.g., triple negative breast cancer cells (HCC1937) and platinum-resistant ovarian cells (SKOV3, A2780cis)). With the IC50 values of 28-80 and 25-44 µg mL-1 of l- and d-dipeptide precursors against cancer cells, respectively, EISA is innocuous to normal cells. Moreover, using coculture of cancer and normal cells, the selectivity of EISA is validated against cancer cells. Besides revealing that intracellular EISA cause apoptosis or necroptosis to kill the cancer cells, this work illustrates a new approach to amplify the enzymatic difference between cancer and normal cells and to expand the pool of drug candidates for potentially overcoming drug resistance in cancer therapy.

Cisplatin Resistant Spheroids Model Clinically Relevant Survival Mechanisms in Ovarian Tumors.

The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified candidate mechanisms and biological pathways associated with cisplatin resistance. OVCAR-8 human ovarian carcinoma cells were exposed to sub-lethal concentrations of cisplatin to create a matched cisplatin-resistant cell line, OVCAR-8R. Genome-wide gene expression profiling of sensitive and resistant ovarian cancer spheroids identified 3,331 significantly differentially expressed probesets coding for 3,139 distinct protein-coding genes (Fc >2, FDR < 0.05) (S2 Table). Despite significant expression changes in some transporters including MDR1, cisplatin resistance was not associated with differences in intracellular cisplatin concentration. Cisplatin resistant cells were significantly enriched for a mesenchymal gene expression signature. OVCAR-8R resistance derived gene sets were significantly more biased to patients with shorter survival. From the most differentially expressed genes, we derived a 17-gene expression signature that identifies ovarian cancer patients with shorter overall survival in three independent datasets. We propose that the use of cisplatin resistant cell lines in 3D spheroid models is a viable approach to gain insight into resistance mechanisms relevant to ovarian tumors in patients. Our data support the emerging concept that ovarian cancers can acquire drug resistance through an epithelial-to-mesenchymal transition.

Enzyme-Instructed Intracellular Molecular Self-Assembly to Boost Activity of Cisplatin against Drug-Resistant Ovarian Cancer Cells.

Anticancer drug resistance demands innovative approaches that boost the activity of drugs against drug-resistant cancers without increasing the systemic toxicity. Here we show the use of enzyme-instructed self-assembly (EISA) to generate intracellular supramolecular assemblies that drastically boost the activity of cisplatin against drug-resistant ovarian cancer cells. We design and synthesize small peptide precursors as the substrates of carboxylesterase (CES). CES cleaves the ester bond pre-installed on the precursors to form the peptides that self-assemble in water to form nanofibers. At the optimal concentrations, the precursors themselves are innocuous to cells, but they double or triple the activity of cisplatin against the drug-resistant ovarian cancer cells. This work illustrates a simple, yet fundamental, new way to introduce non-cytotoxic components into combination therapies with cisplatin without increasing the systemic burden or side effects.