Genome-wide quantification of copy-number aberration impact on gene expression in ovarian high-grade serous carcinoma.

Copy-number alterations (CNAs) are a hallmark of cancer and can regulate cancer cell states via altered gene expression values. Herein, we have developed a copy-number impact (CNI) analysis method that quantifies the degree to which a gene expression value is impacted by CNAs and leveraged this analysis at the pathway level. Our results show that a high CNA is not necessarily reflected at the gene expression level, and our method is capable of detecting genes and pathways whose activity is strongly influenced by CNAs. Furthermore, the CNI analysis enables unbiased categorization of CNA categories, such as deletions and amplifications. We identified six CNI-driven pathways associated with poor treatment response in ovarian high-grade serous carcinoma (HGSC), which we found to be the most CNA-driven cancer across 14 cancer types. The key driver in most of these pathways was amplified wild-type KRAS, which we validated functionally using CRISPR modulation. Our results suggest that wild-type KRAS amplification is a driver of chemotherapy resistance in HGSC and may serve as a potential treatment target.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma.

OBJECTIVES: We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC). MATERIALS AND METHODS: This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis. RESULTS: Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS. CONCLUSIONS: Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer.

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.

QuantISH: RNA in situ hybridization image analysis framework for quantifying cell type-specific target RNA expression and variability.

RNA in situ hybridization (RNA-ISH) is a powerful spatial transcriptomics technology to characterize target RNA abundance and localization in individual cells. This allows analysis of tumor heterogeneity and expression localization, which are not readily obtainable through transcriptomic data analysis. RNA-ISH experiments produce large amounts of data and there is a need for automated analysis methods. Here we present QuantISH, a comprehensive open-source RNA-ISH image analysis pipeline that quantifies marker expressions in individual carcinoma, immune, and stromal cells on chromogenic or fluorescent in situ hybridization images. QuantISH is designed to be modular and can be adapted to various image and sample types and staining protocols. We show that in chromogenic RNA in situ hybridization images of high-grade serous carcinoma (HGSC) QuantISH cancer cell classification has high precision, and signal expression quantification is in line with visual assessment. We further demonstrate the power of QuantISH by showing that CCNE1 average expression and DDIT3 expression variability, as captured by the variability factor developed herein, act as candidate biomarkers in HGSC. Altogether, our results demonstrate that QuantISH can quantify RNA expression levels and their variability in carcinoma cells, and thus paves the way to utilize RNA-ISH technology.

FUNGI: FUsioN Gene Integration toolset.

MOTIVATION: Fusion genes are both useful cancer biomarkers and important drug targets. Finding relevant fusion genes is challenging due to genomic instability resulting in a high number of passenger events. To reveal and prioritize relevant gene fusion events we have developed FUsionN Gene Identification toolset (FUNGI) that uses an ensemble of fusion detection algorithms with prioritization and visualization modules. RESULTS: We applied FUNGI to an ovarian cancer dataset of 107 tumor samples from 36 patients. Ten out of 11 detected and prioritized fusion genes were validated. Many of detected fusion genes affect the PI3K-AKT pathway with potential role in treatment resistance. AVAILABILITYAND IMPLEMENTATION: FUNGI and its documentation are available at https://bitbucket.org/alejandra_cervera/fungi as standalone or from Anduril at https://www.anduril.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PRISM: recovering cell-type-specific expression profiles from individual composite RNA-seq samples.

MOTIVATION: A major challenge in analyzing cancer patient transcriptomes is that the tumors are inherently heterogeneous and evolving. We analyzed 214 bulk RNA samples of a longitudinal, prospective ovarian cancer cohort and found that the sample composition changes systematically due to chemotherapy and between the anatomical sites, preventing direct comparison of treatment-naive and treated samples. RESULTS: To overcome this, we developed PRISM, a latent statistical framework to simultaneously extract the sample composition and cell-type-specific whole-transcriptome profiles adapted to each individual sample. Our results indicate that the PRISM-derived composition-free transcriptomic profiles and signatures derived from them predict the patient response better than the composite raw bulk data. We validated our findings in independent ovarian cancer and melanoma cohorts, and verified that PRISM accurately estimates the composition and cell-type-specific expression through whole-genome sequencing and RNA in situ hybridization experiments. AVAILABILITYAND IMPLEMENTATION: https://bitbucket.org/anthakki/prism. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Agile workflow for interactive analysis of mass cytometry data.

MOTIVATION: Single-cell proteomics technologies, such as mass cytometry, have enabled characterization of cell-to-cell variation and cell populations at a single-cell resolution. These large amounts of data, require dedicated, interactive tools for translating the data into knowledge. RESULTS: We present a comprehensive, interactive method called Cyto to streamline analysis of large-scale cytometry data. Cyto is a workflow-based open-source solution that automates the use of state-of-the-art single-cell analysis methods with interactive visualization. We show the utility of Cyto by applying it to mass cytometry data from peripheral blood and high-grade serous ovarian cancer (HGSOC) samples. Our results show that Cyto is able to reliably capture the immune cell sub-populations from peripheral blood and cellular compositions of unique immune- and cancer cell subpopulations in HGSOC tumor and ascites samples. AVAILABILITYAND IMPLEMENTATION: The method is available as a Docker container at https://hub.docker.com/r/anduril/cyto and the user guide and source code are available at https://bitbucket.org/anduril-dev/cyto. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

qSNE: quadratic rate t-SNE optimizer with automatic parameter tuning for large datasets.

MOTIVATION: Non-parametric dimensionality reduction techniques, such as t-distributed stochastic neighbor embedding (t-SNE), are the most frequently used methods in the exploratory analysis of single-cell datasets. Current implementations scale poorly to massive datasets and often require downsampling or interpolative approximations, which can leave less-frequent populations undiscovered and much information unexploited. RESULTS: We implemented a fast t-SNE package, qSNE, which uses a quasi-Newton optimizer, allowing quadratic convergence rate and automatic perplexity (level of detail) optimizer. Our results show that these improvements make qSNE significantly faster than regular t-SNE packages and enables full analysis of large datasets, such as mass cytometry data, without downsampling. AVAILABILITY AND IMPLEMENTATION: Source code and documentation are openly available at https://bitbucket.org/anthakki/qsne/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ALDH1A1-related stemness in high-grade serous ovarian cancer is a negative prognostic indicator but potentially targetable by EGFR/mTOR-PI3K/aurora kinase inhibitors.

Poor chemotherapy response remains a major treatment challenge for high-grade serous ovarian cancer (HGSC). Cancer stem cells are the major contributors to relapse and treatment failure as they can survive conventional therapy. Our objectives were to characterise stemness features in primary patient-derived cell lines, correlate stemness markers with clinical outcome and test the response of our cells to both conventional and exploratory drugs. Tissue and ascites samples, treatment-naive and/or after neoadjuvant chemotherapy, were prospectively collected. Primary cancer cells, cultured under conditions favouring either adherent or spheroid growth, were tested for stemness markers; the same markers were analysed in tissue and correlated with chemotherapy response and survival. Drug sensitivity and resistance testing was performed with 306 oncology compounds. Spheroid growth condition HGSC cells showed increased stemness marker expression (including aldehyde dehydrogenase isoform I; ALDH1A1) as compared with adherent growth condition cells, and increased resistance to platinum and taxane. A set of eight stemness markers separated treatment-naive tumours into two clusters and identified a distinct subgroup of HGSC with enriched stemness features. Expression of ALDH1A1, but not most other stemness markers, was increased after neoadjuvant chemotherapy and its expression in treatment-naive tumours correlated with chemoresistance and reduced survival. In drug sensitivity and resistance testing, five compounds, including two PI3K-mTOR inhibitors, demonstrated significant activity in both cell culture conditions. Thirteen compounds, including EGFR, PI3K-mTOR and aurora kinase inhibitors, were more toxic to spheroid cells than adherent cells. Our results identify stemness markers in HGSC that are associated with a decreased response to conventional chemotherapy and reduced survival if expressed by treatment-naive tumours. EGFR, mTOR-PI3K and aurora kinase inhibitors are candidates for targeting this cell population. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

A longitudinal analysis of CA125 glycoforms in the monitoring and follow up of high grade serous ovarian cancer.

OBJECTIVE: Cancer antigen 125 (CA125) is generally considered the gold standard of biomarkers in the diagnosis and monitoring of high grade serous ovarian carcinoma (HGSC). We recently reported, that two CA125 glycoforms (CA125-STn and CA125-MGL) have a high specificity to HGSC and further hypothesized, that these cancer specific glycoforms are feasible candidates as biomarkers in HGSC treatment and follow up. METHODS: Our cohort consisted of 122 patients diagnosed with HGSC. Serum samples were collected longitudinally at the time of diagnosis, during treatment and follow up. Serum levels of CA125, CA125-STn and CA125-MGL were determined and compared or correlated with different end points (tumor load assessed intraoperatively, residual disease, treatment response, progression free survival). RESULTS: Serum CA125-STn levels at diagnosis differentiated patients with low tumor load and high tumor load (p = 0,030), indicating a favorable detection of tumor volume. Similarly, the CA125-STn levels at diagnosis were significantly lower in patients with subsequent complete cytoreduction than in patients with suboptimal cytoreduction (p = 0,025). Conventional CA125 did not differentiate these patients (p = 0,363 and p = 0,154). The CA125-STn nadir value predicted the progression free survival of patients. The detection of disease relapse was improved with CA125-STn, which presented higher fold increase in 80,0% of patients and earlier increase in 37,0% of patients. CONCLUSIONS: CA125-STn showed promise as a useful biomarker in the monitoring and follow up of patients with HGSC utilizing a robust and affordable technique. Our findings are topical as a suitable indicator of tumor load facilitates patient selection in an era of new targeted therapies.

HE4 in the evaluation of tumor load and prognostic stratification of high grade serous ovarian carcinoma.

OBJECTIVE: Human epididymis protein 4 (HE4) is a validated, complementary biomarker to cancer antigen 125 (CA125) for high grade serous ovarian carcinoma (HGSC). Currently, there are insufficient data on the utility of longitudinal HE4 measurement during HGSC treatment and follow up. We set to provide a comprehensive analysis on the kinetics and prognostic performance of HE4 with serial measurements during HGSC treatment and follow up. METHODS: This prospective study included 143 patients with advanced HGSC (ClinicalTrials.gov identifier: NCT01276574). Serum CA125 and HE4 were measured at baseline, before each cycle of chemotherapy and during follow up until first progression. Baseline biomarker values were compared to the tumor load assessed during surgery and to residual disease. Biomarker nadir values and concentrations at progression were correlated to survival. RESULTS: The baseline HE4 concentration distinguished patients with a high tumor load from patients with a low tumor load assessed during surgery (p<.0001). The baseline CA125 level was not associated with tumor load to a similar extent (p=.067). At progression, the HE4 level was an independent predictor of worse survival in the multivariate analysis (p=.002). All patients that were alive 3 years post-progression had a serum HE4 concentration below 199.20 pmol/l at the 1st recurrence. CONCLUSION: HE4 is a feasible biomarker in the treatment monitoring and prognostic stratification of patients with HGSC. Specifically, the serum level of HE4 at first relapse was associated with the survival of patients and it may be a useful complementary tool in the selection of second line treatments. This is to the best of our knowledge the first time this finding has been reported.

Identifying differentially methylated sites in samples with varying tumor purity.

Motivation: DNA methylation aberrations are common in many cancer types. A major challenge hindering comparison of patient-derived samples is that they comprise of heterogeneous collection of cancer and microenvironment cells. We present a computational method that allows comparing cancer methylomes in two or more heterogeneous tumor samples featuring differing, unknown fraction of cancer cells. The method is unique in that it allows comparison also in the absence of normal cell control samples and without prior tumor purity estimates, as these are often unavailable or unreliable in clinical samples. Results: We use simulations and next-generation methylome, RNA and whole-genome sequencing data from two cancer types to demonstrate that the method is accurate and outperforms alternatives. The results show that our method adapts well to various cancer types and to a wide range of tumor content, and works robustly without a control or with controls derived from various sources. Availability and implementation: The method is freely available at https://bitbucket.org/anthakki/dmml. Supplementary information: Supplementary data are available at Bioinformatics online.

Hyper-phosphorylation of Sequestosome-1 Distinguishes Resistance to Cisplatin in Patient Derived High Grade Serous Ovarian Cancer Cells.

Platinum-resistance is a major limitation to effective chemotherapy regimens in high-grade serous ovarian cancer (HGSOC). To better understand the mechanisms involved we characterized the proteome and phosphoproteome in cisplatin sensitive and resistant HGSOC primary cells using a mass spectrometry-based proteomic strategy. PCA analysis identified a distinctive phosphoproteomic signature between cisplatin sensitive and resistant cell lines. The most phosphorylated protein in cisplatin resistant cells was sequestosome-1 (p62/SQSTM1). Changes in expression of apoptosis and autophagy related proteins Caspase-3 and SQSTM1, respectively, were validated by Western blot analysis. A significant increase in apoptosis in the presence of cisplatin was observed in only the sensitive cell line while SQSTM1 revealed increased expression in the resistant cell line relative to sensitive cell line. Furthermore, site-specific phosphorylation on 20 amino acid residues of SQSTM1 was detected indicating a hyper-phosphorylation phenotype. This elevated hyper-phosphorylation of SQSTM1 in resistant HGSOC cell lines was validated with Western blot analysis. Immunofluoresence staining of s28-pSQSTM1 showed inducible localization to autophagosomes upon cisplatin treatment in the sensitive cell line while being constitutively expressed to autophagosomes in the resistant cell. Furthermore, SQSTM1 expression was localized in cancer cells of clinical high-grade serous tumors. Here, we propose hyper-phosphorylation of SQSTM1 as a marker and a key proteomic change in cisplatin resistance development in ovarian cancers by activating the autophagy pathway and influencing down-regulation of apoptosis.

18F-FDG-PET/CT based total metabolic tumor volume change during neoadjuvant chemotherapy predicts outcome in advanced epithelial ovarian cancer.

OBJECTIVE: To evaluate the predictive potential of total metabolic tumor volume (MTV) reduction during neoadjuvant chemotherapy (NACT) with 18F-FDG-PET/CT in an advanced FIGO stage III/IV epithelial ovarian cancer (EOC) patient cohort. METHODS: Twenty-nine primarily inoperable EOC patients underwent 18F-FDG-PET/CT before and after NACT. The pre- and post-NACT total MTV, in addition to the percentage MTV reduction during NACT, were compared with primary therapy outcome and progression-free survival (PFS). ROC-analysis determined an optimal threshold for MTV reduction identifying patients with progressive or stable disease (PD/SD) at the end of primary therapy. A multivariate analysis with residual tumor (0/>0), FIGO stage (III/IV) and MTV reduction compared to PFS was performed. The association between MTV reduction and overall survival (OS) was evaluated. RESULTS: The median pre- and post-NACT total MTV were 352 cm3 (range 150 to 1322 cm3) and 51 cm3 (range 0 to 417 cm3), respectively. The median MTV reduction during NACT was 89% (range 24% to 100%). Post-NACT MTV and MTV reduction associated with primary therapy outcome (MTV post-NACT p = 0.007, MTV reduction p = 0.001) and PFS (MTV post-NACT p = 0.005, MTV reduction p = 0.005). MTV reduction <85% identified the PD/SD patients (sensitivity 70%, specificity 78%, AUC 0.79). In a multivariate analysis, MTV reduction (p = 0.002) and FIGO stage (p = 0.003) were statistically significant variables associated with PFS. MTV reduction during NACT corresponded to OS (p = 0.05). CONCLUSION: 18F-FDG-PET/CT is helpful in NACT response evaluation. Patients with total MTV reduction <85% during NACT might be candidates for second-line chemotherapy and clinical trials, instead of interval debulking surgery.

Postoperative human epididymis protein 4 predicts primary therapy outcome in advanced epithelial ovarian cancer.

Primary chemotherapy treatment response monitoring in advanced epithelial ovarian cancer (EOC) is currently based on CT-imaging and serum CA125 values. Serum HE4 profile during first line chemotherapy has not been previously studied. We evaluated the HE4 profile during first line chemotherapy after primary (PDS) and interval debulking surgery (IDS). In total, 49 FIGO stage III/IV EOC patients were included in the study. 22 patients underwent PDS and 27 patients neoadjuvant chemotherapy (NACT) followed by IDS. Serial HE4 and CA125 serum samples were taken during first line chemotherapy. The association of postoperative tumor markers to surgery outcome, primary therapy outcome and progression free survival (PFS) were determined. The lowest HE4 and CA125 values during chemotherapy were compared to primary therapy outcome and PFS. The postoperative HE4 was associated to residual tumor after surgery (p = 0.0001), primary therapy outcome (p = 0.004) and PFS (p = 0.03) in all patients (n = 40). The postoperative CA125 was associated to PFS after IDS (n = 26, p = 0.006), but not after PDS. In multivariate analysis with FIGO stage (III/IV), residual tumor (0/>0) and postoperative CA125, the postoperative HE4 was the only statistically significant prognostic variable predicting PFS. Both HE4 and CA125 nadir corresponded to primary therapy outcome (HE4 p < 0.0001, CA125 p < 0.0001) and PFS (HE4 p = 0.009, CA125 p < 0.0001). HE4 is a promising candidate for EOC response monitoring. In our study, the performance of HE4 in response monitoring of first line chemotherapy was comparable to that of CA125. Of the postoperative values, only HE4 was statistically significantly associated to primary therapy outcome.

Roles of human epididymis protein 4, carbohydrate antigen 125, inhibin B and anti-Müllerian hormone in the differential diagnosis and follow-up of ovarian granulosa cell tumors.

OBJECTIVE: Evaluation of circulating tumor markers in ovarian cancer is crucial for optimal patient care. The goal of this study was to verify the most accurate circulating tumor markers for the diagnosis and follow-up of adult-type granulosa cell tumors (AGCTs). METHODS: The levels of circulating human epididymis protein 4 (HE4) and carbohydrate antigen 125 (CA125), together with AGCT markers inhibin B and anti-Müllerian hormone (AMH), were measured in 135 samples from AGCT patients, 37 epithelial ovarian carcinoma (EOC) patients, and 40 endometrioma (ENDO) patients. The levels were plotted with receiver operating characteristic (ROC) graphs, and the area under the curves (AUC) of the different markers were calculated and compared. RESULTS: HE4 levels were significantly lower in AGCTs than in EOCs (p<0.0001). CA125 levels were above 35IU/l in 25% of AGCT patients and 47.5% of ENDO patients, whereas inhibin B and AMH levels were elevated only in patients with AGCTs. In the AUC comparison analyses, inhibin B alone was sufficient to differentiate AGCT from EOC. In differentiating AGCT from ENDO, inhibin B and AMH performed similarly, and the combination of inhibin B and AMH increased the accuracy compared to either marker alone (sensitivity, 100%; specificity, 93%). Among AGCT patients, inhibin B was the best marker for detecting the presence of AGCT. CONCLUSIONS: HE4 and CA125 levels were low in AGCTs, and inhibin B was the most accurate circulating biomarker in distinguishing AGCTs from EOCs and from ENDOs. Inhibin B was also the best single marker for AGCT follow-up.

A Nanoparticle-Lectin Immunoassay Improves Discrimination of Serum CA125 from Malignant and Benign Sources.

BACKGROUND: Measurement of serum cancer antigen 125 (CA125) is the standard approach for epithelial ovarian cancer (EOC) diagnostics and follow-up. However, the clinical specificity is not optimal because increased values are also detected in healthy controls and in benign diseases. CA125 is known to be differentially glycosylated in EOC, potentially offering a way to construct CA125 assays with improved cancer specificity. Our goal was to identify carbohydrate-reactive lectins for discriminating between CA125 originating from EOC and noncancerous sources. METHODS: CA125 from the OVCAR-3 cancer cell line, placental homogenate, and ascites fluid from patients with cirrhosis were captured on anti-CA125 antibody immobilized on microtitration wells. A panel of lectins, each coated onto fluorescent europium-chelate-doped 97-nm nanoparticles (Eu(+3)-NPs), was tested for detection of the immobilized CA125. Serum samples from high-grade serous EOC or patients with endometriosis and healthy controls were analyzed. RESULTS: By using macrophage galactose-type lectin (MGL)-coated Eu(+3)-NPs, an analytically sensitive CA125 assay (CA125(MGL)) was achieved that specifically recognized the CA125 isoform produced by EOC, whereas the recognition of CA125 from nonmalignant conditions was reduced. Serum CA125(MGL) measurement better discriminated patients with EOC from endometriosis compared to conventional immunoassay. The discrimination was particularly improved for marginally increased CA125 values and for earlier detection of EOC progression. CONCLUSIONS: The new CA125(MGL) assay concept could help reduce the false-positive rates of conventional CA125 immunoassays. The improved analytical specificity of this test approach is dependent on a discriminating lectin immobilized in large numbers on Eu(+3)-NPs, providing both an avidity effect and signal amplification.

18F-FDG-PET/CT can identify histopathological non-responders to platinum-based neoadjuvant chemotherapy in advanced epithelial ovarian cancer.

OBJECTIVE: The aim of this study was to examine the relationship between the reduction of maximum standardized uptake values (SUVmax) in 18F-FDG-PET/CT to histopathological changes obtained with neoadjuvant chemotherapy (NACT) in advanced epithelial ovarian cancer (EOC). We wanted to evaluate whether 18F-FDG-PET/CT is useful for identifying patients who will not respond to NACT and would therefore benefit from second-line chemotherapy instead of interval debulking surgery (IDS). METHODS: Twenty-six primarily inoperable EOC patients treated with NACT were enrolled in this study. 18F-FDG-PET/CT imaging was performed before diagnostic laparoscopy and after three to four NACT cycles. The relationship between the decrease in omental SUVmax from before to after NACT with omental histopathological response was examined in samples taken from the corresponding anatomical sites during IDS. Patients were divided into three groups according to chemotherapy-induced histopathological changes. Serum CA125 and HE4 halftimes during NACT as well as Ki-67 antigen expression in IDS samples were determined. RESULTS: The median omental SUVmax change during NACT was -64% (range-16% to -84%), and it was associated with histopathological response (p=0.004, OR 0.9, CI 0.84-0.97). A SUVmax decrease of less than 57% identified histopathological non-responders. Progression-free survival (PFS) differed between the poor, moderate and good histopathological response groups (0.9 year vs. 1.2 years vs. 1.4 years, respectively, p=0.05). The SUVmax change was not associated with PFS. CONCLUSION: 18F-FDG-PET/CT was able to identify patients who would not respond to NACT. To obtain a histopathological response in EOC, a substantial metabolic response in 18F-FDG-PET/CT is necessary.

Serum HE4 and CA125 as predictors of response and outcome during neoadjuvant chemotherapy of advanced high-grade serous ovarian cancer.

Human epididymis protein 4 (HE4) is a novel tumour marker in epithelial ovarian cancer (EOC). Data on its profile and predictive potential for subsequent outcome after neoadjuvant chemotherapy (NACT) are still under investigation. The aim of this study was to compare CA125 and HE4 profiles with radiologic response after NACT and to evaluate their potential as predictors of clinical outcome in a primarily inoperable EOC patient cohort. Twenty-five EOC patients of high-grade subtype (HGSC) treated with NACT were enrolled in the study. Serum HE4 and CA125 samples were taken at the time of diagnosis and before interval debulking surgery (IDS). Pre-NACT and pre-IDS HE4 and CA125 and their percentage changes were compared with NACT response seen on CT and surgical outcome in IDS. We also evaluated the biomarkers' abilities to predict platinum-free interval (PFI), progression-free survival (PFS) and overall survival (OS). All 25 patients were considered inoperable in laparoscopy at the time of diagnosis. HE4 and CA125 changes during NACT did not correlate with the changes seen on CT. Surgical outcome in IDS was associated with pre-IDS biomarker values but not with those taken before diagnosis. In IDS, 87 % had <1-cm residual tumour. In patients with HE4 change >80 and <80 % during NACT, the median OS was 3.38 and 1.60 years (p = 0.01), respectively. Serum HE4 is a promising additional tool when evaluating advanced HGSC patient's response to NACT. It may be helpful when deciding whether to proceed to IDS or to second-line chemotherapy.

Bexmarilimab Activates Human Tumor-Associated Macrophages to Support Adaptive Immune Responses in Interferon-Poor Immune Microenvironments.

Immune checkpoint inhibitors (ICI) show substantially greater efficacy in inflamed tumors characterized by preexisting T-cell infiltration and IFN signaling than in noninflamed "cold" tumors, which often remain immunotherapy resistant. The cancer immunotherapy bexmarilimab, which inhibits the scavenger receptor Clever-1 to release macrophage immunosuppression and activate adaptive immunity, has shown treatment benefit in subsets of patients with advanced solid malignancies. However, the mechanisms that determine bexmarilimab therapy outcome in individual patients are unknown. Here we characterized bexmarilimab response in ovarian cancer ascites macrophages ex vivo using single-cell RNA sequencing and demonstrated increased IFN signaling and CXCL10 secretion following bexmarilimab treatment. We further showed that bexmarilimab was most efficacious in macrophages with low baseline IFN signaling, as chronic IFNγ priming abolished bexmarilimab-induced TNFα release. These results highlight an approach to target immunologically cold tumors and to increase the likelihood of their subsequent response to ICIs.