Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer.

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

Molecular patterns of resistance to immune checkpoint blockade in melanoma.

Immune checkpoint blockade (ICB) has improved outcome for patients with metastatic melanoma but not all benefit from treatment. Several immune- and tumor intrinsic features are associated with clinical response at baseline. However, we need to further understand the molecular changes occurring during development of ICB resistance. Here, we collect biopsies from a cohort of 44 patients with melanoma after progression on anti-CTLA4 or anti-PD1 monotherapy. Genetic alterations of antigen presentation and interferon gamma signaling pathways are observed in approximately 25% of ICB resistant cases. Anti-CTLA4 resistant lesions have a sustained immune response, including immune-regulatory features, as suggested by multiplex spatial and T cell receptor (TCR) clonality analyses. One anti-PD1 resistant lesion harbors a distinct immune cell niche, however, anti-PD1 resistant tumors are generally immune poor with non-expanded TCR clones. Such immune poor microenvironments are associated with melanoma cells having a de-differentiated phenotype lacking expression of MHC-I molecules. In addition, anti-PD1 resistant tumors have reduced fractions of PD1+ CD8+ T cells as compared to ICB naïve metastases. Collectively, these data show the complexity of ICB resistance and highlight differences between anti-CTLA4 and anti-PD1 resistance that may underlie differential clinical outcomes of therapy sequence and combination.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer.

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

Breast cancer associated CD169+ macrophages possess broad immunosuppressive functions but enhance antibody secretion by activated B cells.

CD169+ resident macrophages in lymph nodes of breast cancer patients are for unknown reasons associated with a beneficial prognosis. This contrasts CD169+ macrophages present in primary breast tumors (CD169+ TAMs), that correlate with a worse prognosis. We recently showed that these CD169+ TAMs were associated with tertiary lymphoid structures (TLSs) and Tregs in breast cancer. Here, we show that CD169+ TAMs can be monocyte-derived and express a unique mediator profile characterized by type I IFNs, CXCL10, PGE2 and inhibitory co-receptor expression pattern. The CD169+ monocyte-derived macrophages (CD169+ Mo-M) possessed an immunosuppressive function in vitro inhibiting NK, T and B cell proliferation, but enhanced antibody and IL6 secretion in activated B cells. Our findings indicate that CD169+ Mo-M in the primary breast tumor microenvironment are linked to both immunosuppression and TLS functions, with implications for future targeted Mo-M therapy.

CD169+ Macrophages in Primary Breast Tumors Associate with Tertiary Lymphoid Structures, Tregs and a Worse Prognosis for Patients with Advanced Breast Cancer.

The presence of CD169+ macrophages in the draining lymph nodes of cancer patients is, for unknown reasons, associated with a beneficial prognosis. We here investigated the prognostic impact of tumor-infiltrating CD169+ macrophages in primary tumors (PTs) and their spatial relation to tumor-infiltrating B and T cells. Using two breast cancer patient cohorts, we show that CD169+ macrophages were spatially associated with the presence of B and T cell tertiary lymphoid-like structures (TLLSs) in both PTs and lymph node metastases (LNMs). While co-infiltration of CD169+/TLLS in PTs correlated with a worse prognosis, the opposite was found when present in LNMs. RNA sequencing of breast tumors further confirmed that SIGLEC1 (CD169) expression was associated with mature tertiary lymphoid structure (TLS), and Treg and Breg signatures. We propose that the negative prognostic value related to CD169+ macrophages in PTs is a consequence of an immunosuppressive tumor environment rich in TLSs, Tregs and Bregs.

A deep tabular data learning model predicting cisplatin sensitivity identifies BCL2L1 dependency in cancer.

Cisplatin, a platinum-based chemotherapeutic agent, is widely used as a front-line treatment for several malignancies. However, treatment outcomes vary widely due to intrinsic and acquired resistance. In this study, cisplatin-perturbed gene expression and pathway enrichment were used to define a gene signature, which was further utilized to develop a cisplatin sensitivity prediction model using the TabNet algorithm. The TabNet model performed better (>80 % accuracy) than all other machine learning models when compared to a wide range of machine learning algorithms. Moreover, by using feature importance and comparing predicted ovarian cancer patient samples, BCL2L1 was identified as an important gene contributing to cisplatin resistance. Furthermore, the pharmacological inhibition of BCL2L1 was found to synergistically increase cisplatin efficacy. Collectively, this study developed a tool to predict cisplatin sensitivity using cisplatin-perturbed gene expression and pathway enrichment knowledge and identified BCL2L1 as an important gene in this setting.

How Reliable Are Gene Expression-Based and Immunohistochemical Biomarkers Assessed on a Core-Needle Biopsy? A Study of Paired Core-Needle Biopsies and Surgical Specimens in Early Breast Cancer.

In early breast cancer, a preoperative core-needle biopsy (CNB) is vital to confirm the malignancy of suspected lesions and for assessing the expression of treatment predictive and prognostic biomarkers in the tumor to choose the optimal treatments, emphasizing the importance of obtaining reliable results when biomarker status is assessed on a CNB specimen. This study aims to determine the concordance between biomarker status assessed as part of clinical workup on a CNB compared to a medically untreated surgical specimen. Paired CNB and surgical specimens from 259 patients that were part of the SCAN-B cohort were studied. The concordance between immunohistochemical (IHC) and gene expression (GEX) based biomarker status was investigated. Biomarkers of interest included estrogen receptor (ER; specifically, the alpha variant), progesterone receptor (PgR), Ki67, HER2, and tumor molecular subtype. In general, moderate to very good correlation in biomarker status between the paired CNB and surgical specimens was observed for both IHC assessment (83-99% agreement, kappa range 0.474-0.917) and GEX assessment (70-97% agreement, kappa range 0.552-0.800), respectively. However, using IHC, 52% of cases with low Ki67 status in the CNB shifted to high Ki67 status in the surgical specimen (McNemar's p = 0.011). Similarly, when using GEX, a significant shift from negative to positive ER (47%) and from low to high Ki67 (16%) was observed between the CNB and surgical specimen (McNemar's p = 0.027 and p = 0.002 respectively). When comparing biomarker status between different techniques (IHC vs. GEX) performed on either CNBs or surgical specimens, the agreement in ER, PgR, and HER2 status was generally over 80% in both CNBs and surgical specimens (kappa range 0.395-0.708), but Ki67 and tumor molecular subtype showed lower concordance levels between IHC and GEX (48-62% agreement, kappa range 0.152-0.398). These results suggest that both the techniques used for collecting tissue samples and analyzing biomarker status have the potential to affect the results of biomarker assessment, potentially also impacting treatment decisions and patient survival outcomes.

RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.

Multigene assays for molecular subtypes and biomarkers can aid management of early invasive breast cancer. Using RNA-sequencing we aimed to develop single-sample predictor (SSP) models for clinical markers, subtypes, and risk of recurrence (ROR). A cohort of 7743 patients was divided into training and test set. We trained SSPs for subtypes and ROR assigned by nearest-centroid (NC) methods and SSPs for biomarkers from histopathology. Classifications were compared with Prosigna in two external cohorts (ABiM, n = 100 and OSLO2-EMIT0, n = 103). Prognostic value was assessed using distant recurrence-free interval. Agreement between SSP and NC for PAM50 (five subtypes) was high (85%, Kappa = 0.78) for Subtype (four subtypes) very high (90%, Kappa = 0.84) and for ROR risk category high (84%, Kappa = 0.75, weighted Kappa = 0.90). Prognostic value was assessed as equivalent and clinically relevant. Agreement with histopathology was very high or high for receptor status, while moderate for Ki67 status and poor for Nottingham histological grade. SSP and Prosigna concordance was high for subtype (OSLO-EMIT0 83%, Kappa = 0.73 and ABiM 80%, Kappa = 0.72) and moderate and high for ROR risk category (68 and 84%, Kappa = 0.50 and 0.70, weighted Kappa = 0.70 and 0.78). Pooled concordance for emulated treatment recommendation dichotomized for chemotherapy was high (85%, Kappa = 0.66). Retrospective evaluation suggested that SSP application could change chemotherapy recommendations for up to 17% of postmenopausal ER+/HER2-/N0 patients with balanced escalation and de-escalation. Results suggest that NC and SSP models are interchangeable on a group-level and nearly so on a patient level and that SSP models can be derived to closely match clinical tests.

Evaluation of multiple transcriptomic gene risk signatures in male breast cancer.

Male breast cancer (BCa) is a rare disease accounting for less than 1% of all breast cancers and 1% of all cancers in males. The clinical management is largely extrapolated from female BCa. Several multigene assays are increasingly used to guide clinical treatment decisions in female BCa, however, there are limited data on the utility of these tests in male BCa. Here we present the gene expression results of 381 M0, ER+ve, HER2-ve male BCa patients enrolled in the Part 1 (retrospective analysis) of the International Male Breast Cancer Program. Using a custom NanoString™ panel comprised of the genes from the commercial risk tests Prosigna®, OncotypeDX®, and MammaPrint®, risk scores and intrinsic subtyping data were generated to recapitulate the commercial tests as described by us previously. We also examined the prognostic value of other risk scores such as the Genomic Grade Index (GGI), IHC4-mRNA and our prognostic 95-gene signature. In this sample set of male BCa, we demonstrated prognostic utility on univariate analysis. Across all signatures, patients whose samples were identified as low-risk experienced better outcomes than intermediate-risk, with those classed as high risk experiencing the poorest outcomes. As seen with female BCa, the concordance between tests was poor, with C-index values ranging from 40.3% to 78.2% and Kappa values ranging from 0.17 to 0.58. To our knowledge, this is the largest study of male breast cancers assayed to generate risk scores of the current commercial and academic risk tests demonstrating comparable clinical utility to female BCa.

MET Expression and Cancer Stem Cell Networks Impact Outcome in High-Grade Serous Ovarian Cancer.

Overexpression of the receptor tyrosine kinase MET has been linked to poor survival in several cancer types, and MET has been suggested to interact with stem cell networks. In vitro studies have further suggested a possible benefit of a combined treatment using PARP and MET inhibitors. We used a tissue microarray (TMA) with 130 samples of advanced-stage high-grade serous fallopian tube/ovarian cancer (HGSC) to investigate the prognostic value of MET protein expression alone and in combination with the stem cell factor SOX2. The possible synergistic effects of a PARP and MET inhibitor treatment were evaluated in two cell lines with BRCA1 or BRCA2 deficiency and in their BRCA1/2-proficient counterparts. Patients with tumors positive for MET had worse overall survival (log-rank test, p = 0.015) compared to patients with MET-negative tumors. The prognostic role of MET was even more prominent in the subgroup of patients with SOX2-negative tumors (p = 0.0081). No synergistic effects of the combined treatment with PARP and MET inhibitors were found in the cell lines examined. We conclude that MET expression could be used as a marker for OS in HGSC and that stemness should be taken into consideration when evaluating the mechanisms of this effect.

Protein Signature Predicts Response to Neoadjuvant Treatment With Chemotherapy and Bevacizumab in HER2-Negative Breast Cancers.

PURPOSE: Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS: In the NeoAva phase II clinical trial, patients (N = 132) with large (≥ 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS: We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P < .001) and in patients with low RCB (P < .001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). CONCLUSION: Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.

Oncogenic translation directs spliceosome dynamics revealing an integral role for SF3A3 in breast cancer.

Splicing is a central RNA-based process commonly altered in human cancers; however, how spliceosomal components are co-opted during tumorigenesis remains poorly defined. Here we unravel the core splice factor SF3A3 at the nexus of a translation-based program that rewires splicing during malignant transformation. Upon MYC hyperactivation, SF3A3 levels are modulated translationally through an RNA stem-loop in an eIF3D-dependent manner. This ensures accurate splicing of mRNAs enriched for mitochondrial regulators. Altered SF3A3 translation leads to metabolic reprogramming and stem-like properties that fuel MYC tumorigenic potential in vivo. Our analysis reveals that SF3A3 protein levels predict molecular and phenotypic features of aggressive human breast cancers. These findings unveil a post-transcriptional interplay between splicing and translation that governs critical facets of MYC-driven oncogenesis.

Distinct mechanisms of resistance to fulvestrant treatment dictate level of ER independence and selective response to CDK inhibitors in metastatic breast cancer.

BACKGROUND: Resistance to endocrine treatment in metastatic breast cancer is a major clinical challenge. Clinical tools to predict both drug resistance and possible treatment combination approaches to overcome it are lacking. This unmet need is mainly due to the heterogeneity underlying both the mechanisms involved in resistance development and breast cancer itself. METHODS: To study the complexity of the mechanisms involved in the resistance to the selective estrogen receptor degrader (SERD) fulvestrant, we performed comprehensive biomarker analyses using several in vitro models that recapitulate the heterogeneity of developed resistance. We further corroborated our findings in tissue samples from patients treated with fulvestrant. RESULTS: We found that different in vitro models of fulvestrant resistance show variable stability in their phenotypes, which corresponded with distinct genomic alterations. Notably, the studied models presented adaptation at different cell cycle nodes to facilitate progression through the cell cycle and responded differently to CDK inhibitors. Cyclin E2 overexpression was identified as a biomarker of a persistent fulvestrant-resistant phenotype. Comparison of pre- and post-treatment paired tumor biopsies from patients treated with fulvestrant revealed an upregulation of cyclin E2 upon development of resistance. Moreover, overexpression of this cyclin was found to be a prognostic factor determining resistance to fulvestrant and shorter progression-free survival. CONCLUSIONS: These data highlight the complexity of estrogen receptor positive breast cancer and suggest that the development of diverse resistance mechanisms dictate levels of ER independence and potentially cross-resistance to CDK inhibitors.

Regulatory T lymphocyte infiltration in metastatic breast cancer-an independent prognostic factor that changes with tumor progression.

BACKGROUND: Patients diagnosed with metastatic breast cancer have poor outcome with a median survival of approximately 2 years. While novel therapeutic options are urgently needed, the great majority of breast cancer research has focused on the primary tumor and less is known about metastatic breast cancer and the prognostic impact of the metastatic tumor microenvironment. Here we investigate the immune landscape in unique clinical material. We explore how the immune landscape changes with metastatic progression and elucidate the prognostic role of immune cells infiltrating primary tumors and corresponding lymph node and more importantly distant metastases. METHODS: Immunohistochemical staining was performed on human breast cancer tissue microarrays from primary tumors (n = 231), lymph node metastases (n = 129), and distant metastases (n = 43). Infiltration levels of T lymphocytes (CD3+), regulatory T lymphocytes (Tregs, FOXP3+), macrophages (CD68+), and neutrophils (NE+) were assessed in primary tumors. T lymphocytes and Tregs were further investigated in lymph node and distant metastases. RESULTS: T lymphocyte and Treg infiltration were the most clinically important immune cell populations in primary tumors. Infiltration of T lymphocytes and Tregs in primary tumors correlated with proliferation (P = 0.007, P = 0.000) and estrogen receptor negativity (P = 0.046, P = 0.026). While both T lymphocyte and Treg infiltration had a negative correlation to luminal A subtype (P = 0.031, P = 0.000), only Treg infiltration correlated to luminal B (P = 0.034) and triple-negative subtype (P = 0.019). In primary tumors, infiltration of T lymphocytes was an independent prognostic factor for recurrence-free survival (HR = 1.77, CI = 1.01-3.13, P = 0.048), while Treg infiltration was an independent prognostic factor for breast cancer-specific survival (HR = 1.72, CI = 1.14-2.59, P = 0.01). Moreover, breast cancer patients with Treg infiltration in their distant metastases had poor post-recurrence survival (P = 0.039). Treg infiltration levels changed with metastatic tumor progression in 50% of the patients, but there was no significant trend toward neither lower nor higher infiltration. CONCLUSION: Treg infiltration could have clinical applicability as a prognostic biomarker, deciphering metastatic breast cancer patients with worse prognosis, and accordingly, could be a suitable immunotherapeutic target for patients with metastatic breast cancer. Importantly, half of the patients had changes in Treg infiltration during the course of metastatic progression emphasizing the need to characterize the metastatic immune landscape.

Homologous Recombination Repair Mechanisms in Serous Endometrial Cancer.

Serous endometrial cancer (SEC) resembles high-grade serous ovarian cancer (HGSOC) genetically and clinically, with recurrent copy number alterations, TP53 mutations and a poor prognosis. Thus, SEC patients may benefit from targeted treatments used in HGSOC, e.g., PARP inhibitors. However, the preclinical and clinical knowledge about SEC is scarce, and the exact role of defective DNA repair in this tumor subgroup is largely unknown. We aimed to outline the prevalence of homologous recombination repair deficiency (HRD), copy-number alterations, and somatic mutations in SEC. OncoScan SNP arrays were applied to 19 tumors in a consecutive SEC series to calculate HRD scores and explore global copy-number profiles and genomic aberrations. Copy-number signatures were established and targeted sequencing of 27 HRD-associated genes was performed. All factors were examined in relation to HRD scores to investigate potential drivers of the HRD phenotype. Ten of the 19 SEC tumors (53%) had an HRD score > 42, considered to reflect an HRD phenotype. Higher HRD score was associated with loss of heterozygosity in key HRD genes, and copy-number signatures associated with non-BRCA1/2 dependent HRD in HGSOC. A high number of SECs display an HRD phenotype. It remains to be elucidated whether this also confers PARP inhibitor sensitivity.

Common Susceptibility Loci for Male Breast Cancer.

BACKGROUND: The etiology of male breast cancer (MBC) is poorly understood. In particular, the extent to which the genetic basis of MBC differs from female breast cancer (FBC) is unknown. A previous genome-wide association study of MBC identified 2 predisposition loci for the disease, both of which were also associated with risk of FBC. METHODS: We performed genome-wide single nucleotide polymorphism genotyping of European ancestry MBC case subjects and controls in 3 stages. Associations between directly genotyped and imputed single nucleotide polymorphisms with MBC were assessed using fixed-effects meta-analysis of 1380 cases and 3620 controls. Replication genotyping of 810 cases and 1026 controls was used to validate variants with P values less than 1 × 10-06. Genetic correlation with FBC was evaluated using linkage disequilibrium score regression, by comprehensively examining the associations of published FBC risk loci with risk of MBC and by assessing associations between a FBC polygenic risk score and MBC. All statistical tests were 2-sided. RESULTS: The genome-wide association study identified 3 novel MBC susceptibility loci that attained genome-wide statistical significance (P < 5 × 10-08). Genetic correlation analysis revealed a strong shared genetic basis with estrogen receptor-positive FBC. Men in the top quintile of genetic risk had a fourfold increased risk of breast cancer relative to those in the bottom quintile (odds ratio = 3.86, 95% confidence interval = 3.07 to 4.87, P = 2.08 × 10-30). CONCLUSIONS: These findings advance our understanding of the genetic basis of MBC, providing support for an overlapping genetic etiology with FBC and identifying a fourfold high-risk group of susceptible men.

SOX2 is a promising predictor of relapse and death in advanced stage high-grade serous ovarian cancer patients with residual disease after debulking surgery.

The transcription factor SOX2 is a well-established and important stem cell marker. Its role in cancer biology remains unclear, but it has been proposed to also be a marker of cancer stem cells. We investigated the role of SOX2 protein expression in women with high-grade serous ovarian cancer (HGSOC) to determine its potential prognostic and treatment predictive value. We constructed a tissue microarray of 130 advanced stage HGSOC tumors with an average of 6 cores each, stained for SOX2 protein expression and evaluated survival outcomes. We also treated two HGSOC cell lines with carboplatin and paclitaxel and measured SOX2 expression by RT-PCR and immunoblotting at different doses and time-points. Among patients with non-radical debulking surgery overall and progression-free survival were shorter for patients with SOX2 positive tumors (mean 26 vs. 39 months, log-rank test: p = .0076, and mean 14 vs. 19 months, p = .055, respectively). Knockdown of SOX2 in cell lines did not affect growth inhibition following chemotherapy treatment. Our results show that SOX2 has a strong prognostic potential among HGSOC patients with residual tumor tissue after debulking surgery and suggest that SOX2 expressing cells remaining after non-radical debulking surgery may constitute a subpopulation of cancer stem cells with greater tumor-initiating potential.

Simvastatin is a potential candidate drug in ovarian clear cell carcinomas.

Ovarian clear cell carcinomas (OCCC) constitute a rare subtype of epithelial ovarian cancer, lacking efficient treatment options. Based on previous studies, we assessed the anti-proliferative effect of simvastatin, a Rho GTPase interfering drug, in three OCCC cell lines: JHOC-5, OVMANA and TOV-21G, and one high-grade serous ovarian cancer (HGSOC) cell line, Caov3. We used the Rho GTPase interfering drug CID-1067700 as a control. All OCCC cell lines were more sensitive to single-agent simvastatin than the HGSOC cells, while all cell lines were less sensitive to CID-1067700 than to simvastatin. Combinations of carboplatin and simvastatin were generally antagonistic. Most treatments inhibited migration, while only simvastatin and CID-1067700 also disrupted actin organization in the OCCC cell lines. All treatments induced a G1 arrest in JHOC-5 and TOV-21G cells. Treatments with simvastatin consistently reduced c-Myc protein expression in all OCCC cell lines and displayed evidence of causing both caspase-mediated apoptotic cell death and autophagic response in a cell line dependent manner. Differences between cell lines in response to the treatments were observed and such differences, including e. g. prior treatment, should be investigated further. Conclusively, simvastatin efficiently controlled OCCC proliferation and migration, thus showing potential as a candidate drug for the treatment of OCCC.

High density of stroma-localized CD11c-positive macrophages is associated with longer overall survival in high-grade serous ovarian cancer.

OBJECTIVE: Pre-clinical studies have identified marker- and tumor compartment-defined functionally distinct macrophage subsets. Our study analyzes marker-defined macrophage subsets in different tumor compartments of high-grade serous ovarian cancer (HGSC). METHODS: A discovery cohort (N = 113) was subjected to immunohistochemistry (IHC) analyses. CD68-positivity was confirmed for CD11c-, CD80- and CD163-positive cells. Subset-marker-positive cells were scored in the total tumor and in four tumor compartments. Correlation analyses investigated co-expression of subsets, relationship to CD8+ cells and survival associations. A validation cohort (N = 121) was used to confirm selected findings from the discovery cohort. RESULTS: CD163-positve cells was the most abundant subtype in all compartments. CD11c and CD163 subsets were strongly correlated with each other in stroma and epithelial areas, whereas CD80 and CD163 were correlated in epithelial areas. CD80 and CD11c in perivascular areas showed low correlations. Strong associations were detected between CD8 and CD80 in the tumor epithelium-dominated areas, and between CD8 and CD11c in stroma areas. High stromal CD11c density was associated with a longer median overall survival in the discovery cohort (HR 0.39; CI 95%, 0.23-0.68; p = 0.001) and in the validation cohort (HR 0.46; CI 95%, 0.22-0.93; p = 0.03). CONCLUSIONS: Our study supports the existence of clinically relevant marker- and localization defined macrophage subsets in HGSC, which are independently regulated. Moreover, it suggests stromal CD11c as a novel prognostic marker in HGSC.

A multiplex biomarker assay improves the diagnostic performance of HE4 and CA125 in ovarian tumor patients.

OBJECTIVE: Survival in epithelial ovarian cancer (EOC) remains poor. Most patients are diagnosed in late stages. Early diagnosis increases the chance of survival. We used the proximity extension assay from Olink Proteomics to search for new protein biomarkers with the potential to improve the diagnostic performance of CA125 and HE4 in patients with ovarian tumors. MATERIAL AND METHODS: Plasma samples were obtained from 180 women with ovarian tumors; 30 cases of benign tumor, 28 cases with borderline tumors, 25 early EOC cases (FIGO stage I) and 97 advanced EOC cases (FIGO stages II-IV). Proteins were measured using the Olink® Oncology II and Inflammation panels. For statistical analyses, patients were categorized into benign tumors versus cancer and benign tumors versus borderline + cancer, respectively. RESULTS: We analyzed 177 biomarkers. Thirty-four proteins had ROC AUC > 0.7 for discrimination between benign tumors and cancer. Fifteen proteins had ROC AUC > 0.7 for discrimination between benign tumors and borderline tumors + cancer. HE4 ranked highest for both comparisons. A reference model with HE4, CA125 and age (AUC 0.838 for benign tumors vs. cancer and AUC 0.770 for benign tumors vs. borderline tumors + cancer) was compared to the reference model with the addition of each of the remaining proteins with AUC > 0.7. ITGAV was the only individual biomarker found to improve diagnostic performance of the reference model, to AUC 0.874 for benign tumors vs. cancer and AUC 0.818 for benign tumors vs. borderline tumors + cancer (p < 0.05). Cross-validation and LASSO regression was combined to select multiple biomarker combinations. The best performing model for discrimination between benign tumors and borderline tumors + cancer was a 6-biomarker combination (HE4, CA125, ITGAV, CXCL1, CEACAM1, IL-10RB) and age (AUC 0.868, sensitivity 0.86 and specificity 0.82, p = 0.016 for comparison with the reference model). CONCLUSION: HE4 was the best performing individual biomarker for discrimination between benign ovarian tumors and EOC including borderline tumors. The addition of other carcinogenesis-related biomarkers in a multiplex biomarker panel can improve the diagnostic performance of the established biomarkers HE4 and CA125.