Discovery of Prognostic Markers for Early-Stage High-Grade Serous Ovarian Cancer by Maldi-Imaging

With regard to relapse and survival, early-stage high-grade serous ovarian (HGSOC) patients comprise a heterogeneous group and there is no clear consensus on first-line treatment. Currently, no prognostic markers are available for risk assessment by standard targeted immunohistochemistry and novel approaches are urgently required. Here, we applied MALDI-imaging mass spectrometry (MALDI-IMS), a new method to identify distinct mass profiles including protein signatures on paraffin-embedded tissue sections. In search of prognostic biomarker candidates, we compared proteomic profiles of primary tumor sections from early-stage HGSOC patients with either recurrent (RD) or non-recurrent disease (N = 4; each group) as a proof of concept study. In total, MALDI-IMS analysis resulted in 7537 spectra from the malignant tumor areas. Using receiver operating characteristic (ROC) analysis, 151 peptides were able to discriminate between patients with RD and non-RD (AUC > 0.6 or 0.7). These results confirm that in using IMS, we could identify new candidates to predict clinical outcome and treatment extent for patients with early-stage HGSOC

Influence of migrant background on patient preference and expectations in breast and gynecological malignancies (NOGGO-expression V study): results of a prospective multicentre study in 606 patients in Germany

Background: An effective cross-cultural doctor-patient communication is vital for health literacy and patient compliance. Building a good relationship with medical staff is also relevant for the treatment decision-making process for cancer patients. Studies about the role of a specific migrant background regarding patient preferences and expectations are lacking. We therefore conducted a multicentre prospective survey to explore the needs and preferences of patients with a migrant background (PMB) suffering from gynecological malignancies and breast cancer to evaluate the quality of doctor-patient communication and cancer management compared to non-migrants (NM). Methods: This multicentre survey recruited patients with primary or recurrence of breast, ovarian, peritoneal, or fallopian tube cancer. The patients either filled out a paper form, participated via an online survey, or were interviewed by trained staff. A 58-item questionnaire was primarily developed in German and then translated into three different languages to reach non-German-speaking patients. Results: A total of 606 patients were included in the study: 54.1% (328) were interviewed directly, 9.1% (55) participated via an online survey, and 36.8% (223) used the paper print version. More than one quarter, 27.4% (166) of the participants, had a migrant background. The majority of migrants and NM were highly satisfied with the communication with their doctors. First-generation migrants (FGM) and patients with breast cancer were less often informed about participation in clinical trials (p < 0.05) and 24.5% of them suggested the help of an interpreter to improve the medical consultation. Second and third-generation migrants (SGM and TGM) experienced more fatigue and nausea than expected. Conclusions: Our results allow the hypothesis that training medical staff in intercultural competence and using disease-related patient information in different languages can improve best supportive care management and quality of life in cancer patients with migrant status

Classification of Molecular Subtypes of High-Grade Serous Ovarian Cancer by MALDI-Imaging.

Despite the correlation of clinical outcome and molecular subtypes of high-grade serous ovarian cancer (HGSOC), contemporary gene expression signatures have not been implemented in clinical practice to stratify patients for targeted therapy. Hence, we aimed to examine the potential of unsupervised matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) to stratify patients who might benefit from targeted therapeutic strategies. Molecular subtyping of paraffin-embedded tissue samples from 279 HGSOC patients was performed by NanoString analysis (ground truth labeling). Next, we applied MALDI-IMS paired with machine-learning algorithms to identify distinct mass profiles on the same paraffin-embedded tissue sections and distinguish HGSOC subtypes by proteomic signature. Finally, we devised a novel approach to annotate spectra of stromal origin. We elucidated a MALDI-derived proteomic signature (135 peptides) able to classify HGSOC subtypes. Random forest classifiers achieved an area under the curve (AUC) of 0.983. Furthermore, we demonstrated that the exclusion of stroma-associated spectra provides tangible improvements to classification quality (AUC = 0.988). Moreover, novel MALDI-based stroma annotation achieved near-perfect classifications (AUC = 0.999). Here, we present a concept integrating MALDI-IMS with machine-learning algorithms to classify patients according to distinct molecular subtypes of HGSOC. This has great potential to assign patients for personalized treatment

Quality-adjusted time without symptoms of disease or toxicity and quality-adjusted progression-free survival with niraparib maintenance in first-line ovarian cancer in the PRIMA trial

Background: The PRIMA phase 3 trial showed niraparib significantly prolongs median progression-free survival (PFS) versus placebo in patients with advanced ovarian cancer (OC) responsive to first-line platinum-based chemotherapy, including those who had tumors with homologous recombination deficiency (HRd). This analysis of PRIMA examined the quality-adjusted PFS (QA-PFS) and quality-adjusted time without symptoms of disease or toxicity (Q-TWiST) of patients on maintenance niraparib versus placebo. Methods: Patients were randomized 2:1 to receive once-daily maintenance niraparib (n = 487) or placebo (n = 246). QA-PFS was defined as the PFS of patients adjusted for their health-related quality of life (HRQoL) prior to disease progression, measured using European Quality of Life Five-Dimension (EQ-5D) questionnaire index scores from the PRIMA trial. Q-TWiST was calculated by combining data on PFS, duration of symptomatic grade ⩾2 adverse events (fatigue or asthenia, nausea, vomiting, abdominal pain, and abdominal bloating) prior to disease progression, and EQ-5D index scores. Analyses used data collected up to the last date of PFS assessment (May 17, 2019). Results: The restricted mean QA-PFS was significantly longer with niraparib versus placebo in the HRd (n = 373) and overall intention-to-treat (ITT; n = 733) populations (mean gains of 6.5 [95% confidence interval; CI, 3.9–8.9] and 4.1 [95% CI, 2.2–5.8] months, respectively). There were also significant improvements in restricted mean Q-TWiST for niraparib versus placebo (mean gains of 5.9 [95% CI, 3.5–8.6] and 3.5 [95% CI, 1.7–5.6] months, respectively) in the HRd and ITT populations. Conclusions: In patients with advanced OC, first-line niraparib maintenance was associated with significant gains in QA-PFS and Q-TWiST versus placebo. These findings demonstrate that niraparib maintenance treatment is associated with a PFS improvement and that treatment benefit is maintained even when HRQoL and/or toxicity data are combined with PFS in a single measure. Trial registration: ClinicalTrials.gov: NCT02655016; trial registration date: January 13, 2016 Plain language summary: Background: In a large clinical trial called PRIMA, patients with advanced cancer of the ovary (ovarian cancer) were given either niraparib (a type of cancer medicine) or placebo (a pill containing no medicine/active substances) after having chemotherapy (another type of cancer medicine). Taking niraparib after chemotherapy is called maintenance therapy and aims to give patients more time before their cancer returns or gets worse than if they were not given any further treatment. In the PRIMA trial, patients who took niraparib did have more time before their cancer progressed than if they took placebo. However, it is important to consider patients’ quality of life, which can be made worse by cancer symptoms and/or side effects of treatment. Here, we assessed the overall benefit of niraparib for patients in PRIMA. Methods: Both the length of time before disease progression (or survival time) and quality of life were considered using two different analyses: ● The first analysis was called quality-adjusted PFS (QA-PFS) and looked at how long patients survived with good quality of life. ● The second analysis was called quality-adjusted time without symptoms of disease or toxicity (Q-TWiST) and looked at how long patients survived without cancer symptoms or treatment side effects. Results: The PRIMA trial included 733 patients; 487 took niraparib and 246 took placebo. Around half of the patients in both groups had a type of ovarian cancer that responds particularly well to drugs like niraparib – they are known as homologous recombination deficiency (HRd) patients. ● When information on quality of life (collected from patient questionnaires) and survival was combined in the QA-PFS analysis, HRd patients who took niraparib had approximately 6.5 months longer with a good quality of life before disease progression than those who took placebo. In the overall group of patients (including HRd patients and non-HRd patients), those who took niraparib had approximately 4 months longer than with placebo. ● Using the second analysis (Q-TWiST) to combine information on survival with cancer symptoms and treatment side effects, the HRd patients taking niraparib had approximately 6 months longer without cancer symptoms or treatment side effects (such as nausea or vomiting) than patients taking placebo. In the overall group of patients, those taking niraparib had approximately 3.5 months longer without these cancer symptoms/side effects than patients receiving placebo. Conclusions: These results show that the survival benefits of niraparib treatment remain when accounting for patients’ quality of life. These benefits were seen not only in HRd patients who are known to respond better to niraparib, but in the overall group of patients who took niraparib.publishedVersionPeer reviewe

Characterisation of tumor microvessel density during progression of high-grade serous ovarian cancer: clinico-pathological impact. An OCTIPS Consortium study.

Background: High-grade serous ovarian cancer (HGSOC) intratumoural vasculature evolution remains unknown. The study investigated changes in tumour microvessel density (MVD) in a large cohort of paired primary and recurrent HGSOC tissue samples and its impact on patients’ clinico-pathological outcome. Methods: A total of 222 primary (pOC) and recurrent (rOC) intra-patient paired HGSOC were assessed for immunohistochemical expression of angiogenesis-associated biomarkers (CD31, to evaluate MVD, and VEGF-A). Expression profiles were compared between pOCs and rOCs and correlated with patients' data. Results: High intratumoural MVD and VEGF-A expression were observed in 75.7% (84/111) and 20.7% (23/111) pOCs, respectively. MVDhighand VEGF(+)samples were detected in 51.4% (57/111) and 20.7% (23/111) rOCs, respectively. MVDhigh/VEGF(+)co-expression was found in 19.8% (22/111) and 8.1% (9/111) of pOCs and rOCs, respectively (p = 0.02). Pairwise analysis showed no significant change in MVD (p = 0.935) and VEGF-A (p = 0.121) levels from pOCs to rOCs. MVDhighpOCs were associated with higher CD3(+)(p = 0.029) and CD8(+)(p = 0.013) intratumoural effector TILs, while VEGF(+)samples were most frequently encountered among BRCA-mutated tumours (p = 0.019). Multivariate analysis showed VEGF and MVD were not independent prognostic factors for OS. Conclusions: HGSOC intratumoural vasculature did not undergo significant changes during disease progression. High concentration of CD31(+)vessels seems to promote recruitment of effector TILs. The study also provides preliminary evidence of the correlation between VEGF-positivity and BRCA status

The importance of importance

We define the notion ofimportanceof prognostic factors in studies of survival, and suggest quantifying it by the Schemper-Henderson measure of explained variation. Conceptual differences to the standard approach for the statistical analysis of oncologic studies of survival are discussed and exemplified by means of a study of ovarian cancer. Explained variation permits to establish a ranking of theimportanceof factors, also if measured on different scales, or of different types (dichotomous, qualitative or continuous), and permits to compare groups of related factors. In practice theimportanceof prognostic factors often is disappointingly low. From this it follows that even strong and highly significant prognostic factors often do not translate into close determination of individual survival of patients.status: publishe

In Situ <i>N</i>-Glycosylation Signatures of Epithelial Ovarian Cancer Tissue as Defined by MALDI Mass Spectrometry Imaging

The particularly high mortality of epithelial ovarian cancer (EOC) is in part linked to limited understanding of its molecular signatures. Although there are data available on in situ N-glycosylation in EOC tissue, previous studies focused primarily on neutral N-glycan species and, hence, still little is known regarding EOC tissue-specific sialylation. In this proof-of-concept study, we implemented MALDI mass spectrometry imaging (MALDI-MSI) in combination with sialic acid derivatization to simultaneously investigate neutral and sialylated N-glycans in formalin-fixed paraffin-embedded tissue microarray specimens of less common EOC histotypes and non-malignant borderline ovarian tumor (BOT). The applied protocol allowed detecting over 50 m/z species, many of which showed differential tissue distribution. Most importantly, it could be demonstrated that α2,6- and α2,3-sialylated N-glycans are enriched in tissue regions corresponding to tumor and adjacent tumor-stroma, respectively. Interestingly, analogous N-glycosylation patterns were observed in tissue cores of BOT, suggesting that regio-specific N-glycan distribution might occur already in non-malignant ovarian pathologies. All in all, our data provide proof that the combination of MALDI-MSI and sialic acid derivatization is suitable for delineating regio-specific N-glycan distribution in EOC and BOT tissues and might serve as a promising strategy for future glycosylation-based biomarker discovery studies

In Silico Analysis Predicts Nuclear Factors NR2F6 and YAP1 as Mesenchymal Subtype-Specific Therapeutic Targets for Ovarian Cancer Patients

Background: Tumour heterogeneity in high-grade serous ovarian cancer (HGSOC) is a proposed cause of acquired resistance to treatment and high rates of relapse. Among the four distinct molecular subtypes of HGSOC, the mesenchymal subtype (MES) has been observed with high frequency in several study cohorts. Moreover, it exhibits aggressive characteristics with poor prognosis. The failure to adequately exploit such subtypes for treatment results in high mortality rates, highlighting the need for effective targeted therapeutic strategies that follow the idea of personalized medicine (PM). Methods: As a proof-of-concept, bulk and single-cell RNA data were used to characterize the distinct composition of the tumour microenvironment (TME), as well as the cell–cell communication and its effects on downstream transcription of MES. Moreover, transcription factor activity contextualized with causal inference analysis identified novel therapeutic targets with potential causal impact on transcription factor dysregulation promoting the malignant phenotype. Findings: Fibroblast and macrophage phenotypes are of utmost importance for the complex intercellular crosstalk of MES. Specifically, tumour-associated macrophages were identified as the source of interleukin 1 beta (IL1B), a signalling molecule with significant impact on downstream transcription in tumour cells. Likewise, signalling molecules tumour necrosis factor (TNF), transforming growth factor beta (TGFB1), and C-X-C motif chemokine 12 (CXCL12) were prominent drivers of downstream gene expression associated with multiple cancer hallmarks. Furthermore, several consistently hyperactivated transcription factors were identified as potential sources for treatment opportunities. Finally, causal inference analysis identified Yes-associated protein 1 (YAP1) and Nuclear Receptor Subfamily 2 Group F Member 6 (NR2F6) as novel therapeutic targets in MES, verified in an independent dataset. Interpretation: By utilizing a sophisticated bioinformatics approach, several candidates for treatment opportunities, including YAP1 and NR2F6 were identified. These candidates represent signalling regulators within the cellular network of the MES. Hence, further studies to confirm these candidates as potential targeted therapies in PM are warranted