Tumor-infiltrating lymphocytes in HER2-positive breast cancer treated with neoadjuvant chemotherapy and dual HER2-blockade

Tumor-infiltrating lymphocytes (TILs) have been associated with outcomes in HER2-positive breast cancer patients treated with neoadjuvant chemotherapy and trastuzumab. However, it remains unclear if TILs could be a prognostic and/or predictive biomarker in the context of dual HER2-targeting treatment. In this study, we evaluated the association between TILs and pathological response (pCR) and invasive-disease free survival (IDFS) in 389 patients with stage II-III HER2 positive breast cancer who received neoadjuvant anthracycline-containing or anthracycline-free chemotherapy combined with trastuzumab and pertuzumab in the TRAIN-2 trial. Although no significant association was seen between TILs and pCR, patients with TIL scores ≥60% demonstrated an excellent 3-year IDFS of 100% (95% CI 100-100), regardless of hormone receptor status, nodal stage and attainment of pCR. Additionally, in patients with hormone receptor positive disease, TILs as a continuous variable showed a trend to a positive association with pCR (adjusted Odds Ratio per 10% increase in TILs 1.15, 95% CI 0.99-1.34, p = 0.070) and IDFS (adjusted Hazard Ratio per 10% increase in TILs 0.71, 95% CI 0.50-1.01, p = 0.058). We found no interactions between TILs and anthracycline treatment. Our results suggest that high TIL scores might be able to identify stage II-III HER2-positive breast cancer patients with a favorable prognosis.

B-cells and regulatory T-cells in the microenvironment of HER2+ breast cancer are associated with decreased survival: a real-world analysis of women with HER2+ metastatic breast cancer

BACKGROUND

Despite major improvements in treatment of HER2-positive metastatic breast cancer (MBC), only few patients achieve complete remission and remain progression free for a prolonged time. The tumor immune microenvironment plays an important role in the response to treatment in HER2-positive breast cancer and could contain valuable prognostic information. Detailed information on the cancer-immune cell interactions in HER2-positive MBC is however still lacking. By characterizing the tumor immune microenvironment in patients with HER2-positive MBC, we aimed to get a better understanding why overall survival (OS) differs so widely and which alternative treatment approaches may improve outcome.

METHODS

We included all patients with HER2-positive MBC who were treated with trastuzumab-based palliative therapy in the Netherlands Cancer Institute between 2000 and 2014 and for whom pre-treatment tissue from the primary tumor or from metastases was available. Infiltrating immune cells and their spatial relationships to one another and to tumor cells were characterized by immunohistochemistry and multiplex immunofluorescence. We also evaluated immune signatures and other key pathways using next-generation RNA-sequencing data. With nine years median follow-up from initial diagnosis of MBC, we investigated the association between tumor and immune characteristics and outcome.

RESULTS

A total of 124 patients with 147 samples were included and evaluated. The different technologies showed high correlations between each other. T-cells were less prevalent in metastases compared to primary tumors, whereas B-cells and regulatory T-cells (Tregs) were comparable between primary tumors and metastases. Stromal tumor-infiltrating lymphocytes in general were not associated with OS. The infiltration of B-cells and Tregs in the primary tumor was associated with unfavorable OS. Four signatures classifying the extracellular matrix of primary tumors showed differential survival in the population as a whole.

CONCLUSIONS

In a real-world cohort of 124 patients with HER2-positive MBC, B-cells, and Tregs in primary tumors are associated with unfavorable survival. With this paper, we provide a comprehensive insight in the tumor immune microenvironment that could guide further research into development of novel immunomodulatory strategies.

Characterization of the Tumor Microenvironment of De Novo Oligometastatic Breast Cancer in a Nationwide Cohort

PURPOSE

Oligometastatic breast cancer (OMBC) has a more favorable outcome than widespread metastatic breast cancer. Some patients with OMBC achieve long-term remission if treated with multimodality therapy, including systemic and locally ablative therapies. However, not all patients with OMBC benefit from such treatment, while all experience toxicity. To explore biomarkers identifying patients with OMBC and potential long-term survival, we compared tumor-immune characteristics of patients with OMBC and long-term versus shorter-term survival.

MATERIALS AND METHODS

We collected tumor tissue of 97 patients with de novo OMBC (≤5 metastases) via the Dutch nationwide cancer and pathology registries using a case-control design. Long-term survivors (LTS) were defined as patients alive ≥10 years since OMBC diagnosis. Fifty-five LTS and 42 shorter-term survivors (STS) were included. Median follow-up was 15 years (IQR, 14-16). Tumor characteristics and infiltrating immune cells were assessed by immunohistochemistry and next-generation RNA-sequencing. Association of the resulting 52 biomarkers with long-term survival was assessed using logistic regression. Associations with survival within LTS were assessed using Cox-proportional hazards modeling. P values were adjusted for multiple hypothesis testing.

RESULTS

Most patients had estrogen receptor (ER)-positive OMBC (n = 86; 89%) and 23 (24%) had human epidermal growth factor receptor 2-positive disease. ER positivity in primary tumors distinguished LTS from STS. In addition, extracellular matrix (ECM)2-low and ECM4-high distinguished between long-term and shorter-term survival. Immune levels in the primary tumor did not associate with LTS. However, within the LTS subset, higher immune levels associated with improved progression-free survival.

CONCLUSION

We identified tumor and ECM features in the primary tumor of patients with de novo OMBC that were associated with long-term survival. Our data should be validated in other patients with OMBC before they can be used in clinical practice.

Extensive preclinical validation of combined RMC-4550 and LY3214996 supports clinical investigation for KRAS mutant pancreatic cancer

Over 90% of pancreatic cancers present mutations in KRAS, one of the most common oncogenic drivers overall. Currently, most KRAS mutant isoforms cannot be targeted directly. Moreover, targeting single RAS downstream effectors induces adaptive resistance mechanisms. We report here on the combined inhibition of SHP2, upstream of KRAS, using the allosteric inhibitor RMC-4550 and of ERK, downstream of KRAS, using LY3214996. This combination shows synergistic anti-cancer activity in vitro, superior disruption of the MAPK pathway, and increased apoptosis induction compared with single-agent treatments. In vivo, we demonstrate good tolerability and efficacy of the combination, with significant tumor regression in multiple pancreatic ductal adenocarcinoma (PDAC) mouse models. Finally, we show evidence that ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) can be used to assess early drug responses in animal models. Based on these results, we will investigate this drug combination in the SHP2 and ERK inhibition in pancreatic cancer (SHERPA; ClinicalTrials.gov: NCT04916236) clinical trial, enrolling patients with KRAS-mutant PDAC.

Comprehensive multiplexed immune profiling of the ductal carcinoma in situ immune microenvironment regarding subsequent ipsilateral invasive breast cancer risk

Background

Ductal carcinoma in situ (DCIS) is treated to prevent subsequent ipsilateral invasive breast cancer (iIBC). However, many DCIS lesions will never become invasive. To prevent overtreatment, we need to distinguish harmless from potentially hazardous DCIS. We investigated whether the immune microenvironment (IME) in DCIS correlates with transition to iIBC.

Methods

Patients were derived from a Dutch population-based cohort of 10,090 women with pure DCIS with a median follow-up time of 12 years. Density, composition and proximity to the closest DCIS cell of CD20⁺ B-cells, CD3⁺CD8⁺ T-cells, CD3⁺CD8⁻ T-cells, CD3⁺FOXP3⁺ regulatory T-cells, CD68⁺ cells, and CD8⁺Ki67⁺ T-cells was assessed with multiplex immunofluorescence (mIF) with digital whole-slide analysis and compared between primary DCIS lesions of 77 women with subsequent iIBC (cases) and 64 without (controls).

Results

Higher stromal density of analysed immune cell subsets was significantly associated with higher grade, ER negativity, HER-2 positivity, Ki67 ≥ 14%, periductal fibrosis and comedonecrosis (P < 0.05). Density, composition and proximity to the closest DCIS cell of all analysed immune cell subsets did not differ between cases and controls.

Conclusion

IME features analysed by mIF in 141 patients from a well-annotated cohort of pure DCIS with long-term follow-up are no predictors of subsequent iIBC, but do correlate with other factors (grade, ER, HER2 status, Ki-67) known to be associated with invasive recurrences.

Genetic and compound screens uncover factors modulating cancer cell response to indisulam

The authors identify that loss of SRPK1 sensitises cancer cells to indisulam treatment and loss of CAND1 confers resistance. Resistance is mediated through RBM39. Furthermore, pharmacological Bcl-xL inhibition prevents acquired resistance to indisulam.

Discovering biomarkers of drug response and finding powerful drug combinations can support the reuse of previously abandoned cancer drugs in the clinic. Indisulam is an abandoned drug that acts as a molecular glue, inducing degradation of splicing factor RBM39 through interaction with CRL4^DCAF15. Here, we performed genetic and compound screens to uncover factors mediating indisulam sensitivity and resistance. First, a dropout CRISPR screen identified SRPK1 loss as a synthetic lethal interaction with indisulam that can be exploited therapeutically by the SRPK1 inhibitor SPHINX31. Moreover, a CRISPR resistance screen identified components of the degradation complex that mediate resistance to indisulam: DCAF15, DDA1, and CAND1. Last, we show that cancer cells readily acquire spontaneous resistance to indisulam. Upon acquiring indisulam resistance, pancreatic cancer (Panc10.05) cells still degrade RBM39 and are vulnerable to BCL-xL inhibition. The better understanding of the factors that influence the response to indisulam can assist rational reuse of this drug in the clinic.

Beyond the snapshot: optimizing prognostication and prediction by moving from fixed to functional multidimensional cancer pathology

The role of pathology in patient management has evolved over time from the retrospective review of cells, tissue, and disease (‘what happened’) to a prospective outlook (‘what will happen’). Examination of a static, two‐dimensional hematoxylin and eosin (H&E)‐stained tissue slide has traditionally been the pathologist's primary task, but novel ancillary techniques enabled by technological breakthroughs have supported pathologists in their increasing ability to predict disease status and behaviour. Nevertheless, the informational limits of 2D, fixed tissue are now being reached and technological innovation is urgently needed to ensure that our understanding of disease entities continues to support improved individualized treatment options. Here we review pioneering work currently underway in the field of cancer pathology that has the potential to capture information beyond the current basic snapshot. A selection of exciting new technologies is discussed that promise to facilitate integration of the functional and multidimensional (space and time) information needed to optimize the prognostic and predictive value of cancer pathology. Learning how to analyse, interpret, and apply the wealth of data acquired by these new approaches will challenge the knowledge and skills of the pathology community. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The Cancer SENESCopedia: A delineation of cancer cell senescence

Cellular senescence is characterized as a stable proliferation arrest that can be triggered by multiple stresses. Most knowledge about senescent cells is obtained from studies in primary cells. However, senescence features may be different in cancer cells, since the pathways that are involved in senescence induction are often deregulated in cancer. We report here a comprehensive analysis of the transcriptome and senolytic responses in a panel of 13 cancer cell lines rendered senescent by two distinct compounds. We show that in cancer cells, the response to senolytic agents and the composition of the senescence-associated secretory phenotype are more influenced by the cell of origin than by the senescence trigger. Using machine learning, we establish the SENCAN gene expression classifier for the detection of senescence in cancer cell samples. The expression profiles and senescence classifier are available as an interactive online Cancer SENESCopedia.

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Senescent cancer cells respond differently to senolytic ABT-263

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SASP expression in cancer is heterogeneous and influenced by cell origin

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The SENCAN classifier detects cancer cell senescence in vitro

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The Cancer SENESCopedia contains transcriptome data from 37 senescence models

Breast adipocyte size associates with ipsilateral invasive breast cancer risk after ductal carcinoma in situ

Although ductal carcinoma in situ (DCIS) is a non-obligate precursor to ipsilateral invasive breast cancer (iIBC), most DCIS lesions remain indolent. Hence, overdiagnosis and overtreatment of DCIS is a major concern. There is an urgent need for prognostic markers that can distinguish harmless from potentially hazardous DCIS. We hypothesised that features of the breast adipose tissue may be associated with risk of subsequent iIBC. We performed a case-control study nested in a population-based DCIS cohort, consisting of 2658 women diagnosed with primary DCIS between 1989 and 2005, uniformly treated with breast conserving surgery (BCS) alone. We assessed breast adipose features with digital pathology (HALO®, Indica Labs) and related these to iIBC risk in 108 women that developed subsequent iIBC (cases) and 168 women who did not (controls) by conditional logistic regression, accounting for clinicopathological and immunohistochemistry variables. Large breast adipocyte size was significantly associated with iIBC risk (odds ratio (OR) 2.75, 95% confidence interval (95% CI) = 1.25-6.05). High cyclooxygenase (COX)-2 protein expression in the DCIS cells was also associated with subsequent iIBC (OR 3.70 (95% CI = 1.59-8.64). DCIS with both high COX-2 expression and large breast adipocytes was associated with a 12-fold higher risk (OR 12.0, 95% CI = 3.10-46.3, P < 0.001) for subsequent iIBC compared with women with smaller adipocyte size and low COX-2 expression. Large breast adipocytes combined with high COX-2 expression in DCIS is associated with a high risk of subsequent iIBC. Besides COX-2, adipocyte size has the potential to improve clinical management in patients diagnosed with primary DCIS.

Abstract P6-15-07: Impact of increased mammary adiposity on DCIS progression

Background: The incidence of ductal carcinoma in situ (DCIS) has greatly increased since the introduction of mammographic screening. However, so far, it is still not possible to predict which patient with DCIS will further develop invasive breast cancer. Adipocyte hypertrophy and adipocyte inflammation has been associated with increased risk of developing breast cancer in postmenopausal women and with worse prognosis in breast cancer patients. In this study, we aimed 1) at evaluating the association between mammary adiposity, as assessed by digital pathology, with DCIS progression using a unique case-control series with long-term follow up and 2) study the interaction between DCIS cells and the surrounding adipocytes. Patients and methods: Mammary adipocyte size was measured in surgical specimens of 279 women with primary DCIS. These mammary adipocyte measurements were compared in 109 women with primary DCIS who subsequently developed ipsilateral invasive breast cancer (iIBC) (cases) and 170 women who did not (controls). Patients were matched for age and follow-up duration. Median follow-up time was 12.8 years. Post-menopausal patients were defined as &gt;50 years at diagnosis and represented 220/279 (78,9%) of patients. All patients were treated with breast cancer-conserving surgery only. Intact adipocytes distant from the DCIS lesions were measured (largest diameter and area) using HALO™ image analysis software (Indica Labs, Corrales, NM) on H&E-stained whole slide images of primary DCIS. Given the specific interest in the larger adipocytes, we systematically considered the 75th percentile as unique value for each patient. An average of 4259 adipocytes (min:70, max:21107) was measured per patient. Tissue segmentation was used to measure the adipose area. Adipose triglyceride lipase (ATGL clone 2138, Cell Signaling) immunohistochemistry (IHC) was applied to study ATGL expression in DCIS cells. Her2, ER and COX-2 IHC and RNAseq of microdissected pure DCIS was already available for this series (LL. Visser et al. Clin Can Res 24 (15) 2018). Conditional logistic regression was applied to investigate differences in adipocyte hypertrophy between groups of patients (e.g., cases and controls). Results: Adipocytes were larger and the proportion of adipose tissue was higher in post-menopausal patients (both p&lt;0.001). Mean adipocyte maximum diameter and mean adipocyte area of the 75th percentile ranged from 46.9-115.9 µm and 2016-11336 µm2 respectively. For every 1000 µm2 increase in mean adipocyte area a DCIS patient had a 1.18 increased risk for iIBC (95% CI 1.02-1.36, p= 0.028). DCIS patients with large adipocytes (above the 75th percentile) had a 2.1 increased risk for developing iIBC (95% CI: 1.18-3.72, p=0.011). This observation remained when restricting the analysis to post-menopausal patients (OR 1.19 per 1000 µm2 95% CI 1.01-1.40, p=0.038 and adipocytes above 75th percentile OR 2.2, 95% CI 1.22-3.99, p= 0.009). To further explore the potential interactions between the epithelial cells from DCIS with the adjacent adipocytes, we compared the size of the DCIS-adjacent adipocytes to those away from DCIS lesions. DCIS-adjacent adipocytes showed a reduction in size, suggesting delipidation. Adipose triglyceride lipase (ATGL) is a rate limiting lipase that can release stored free fatty acids (FFA) in DCIS cells for fatty acid ß-oxidation. In a pilot series strong ATGL expression was observed in a subset of DCIS lesions (4 of 25). Conclusion and perspective: This study is the first to demonstrate that mammary adipocyte hypertrophy is associated with an increased risk of progression for patients with DCIS. Our findings might help to distinguish potentially hazardous from harmless DCIS, enabling overtreatment of indolent DCIS. Adipocyte size will be correlated to immunohistochemical expression of ATGL, Her2, ER and COX2 in DCIS, and RNAseq data of pure microdissected DCIS.

Citation Format: Mathilde Matthea Machteld Almekinders, Michael Schaapveld, Bram Thijssen, Ingrid Hofland, Marjolijn Mertz, Dennis Peters, Annegien Broeks, Lodewijk Wessels, Wilbert Zwart, Jos Jonkers, Esther Lips, Christine Desmedt, Jelle Wesseling, on behalf of the PRECISION Team. Impact of increased mammary adiposity on DCIS progression [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-15-07.

Pilot Study to Predict Pharmacokinetics of a Therapeutic Gemcitabine Dose From a Microdose

Microdose studies are exploratory trials to determine early drug pharmacokinetics in humans. In this trial we examined whether the pharmacokinetics of gemcitabine at a therapeutic dose could be predicted from the pharmacokinetics of a microdose. In this prospective, open-label microdosing study, a gemcitabine microdose (100 µg) was given intravenously to participants on day 1, followed by a therapeutic dose (1250 mg/m² ) on day 2. Gemcitabine and its metabolite 2',2'-difluorodeoxyuracil (dFdU) were quantified in plasma and intracellularly by using liquid chromatography-mass spectrometry). Noncompartmental pharmacokinetic analysis was performed. Ten patients participated in this study. The mean area under the plasma concentration-time curve (AUC_0-8 ) of gemcitabine after microdosing was 0.00074 h·mg/L and after therapeutic dosing was 16 h·mg/L. The mean AUC_0-8 of dFdU following the microdose and therapeutic dose were 0.022 h·mg/L and 169 h·mg/L, respectively. Exposure to gemcitabine after the therapeutic dose was within 2-fold of the exposure following a microdose, when linearly extrapolated to 1250 mg/m² . However, the shape of the concentration-time curve was different, as reflected by poor scalability in volume of distribution (939 L versus 222 L). Furthermore, intracellularly phosphorylated gemcitabine and phosphorylated dFdU levels could not be predicted from the microdose. The AUC_0-8 of gemcitabine at therapeutic dose was accurately predicted by the pharmacokinetics of a microdose, when linearly extrapolated to 1250 mg/m² . Volume of distribution, elimination rate constant, and intracellular pharmacokinetics of the therapeutic dose could not be predicted from the microdose, which demonstrates limitations of the microdose approach in this case.

Abstract 2806: Progression of ductal carcinoma in situ (DCIS), is it in the immune microenvironment

Introduction: DCIS is a non-obligate precursor to invasive breast cancer (IBC). DCIS patients are treated similarly to breast cancer with surgery, often followed by radiotherapy and/or endocrine treatment. However, most DCIS lesions will never progress to IBC, indicating that overdiagnosis and overtreatment exists. DCIS lesions show variable amounts of immune cells, particularly in the periductal stroma. Immune escape might be a critical step for transition from DCIS to IBC. We aim to identify factors within the immune microenvironment of DCIS lesions that distinguish harmless from potentially hazardous DCIS.

Methods: A case-control study is being conducted consisting of women with pure DCIS diagnosed between 1989-2005 with median follow-up of 12 years, treated with breast conserving surgery only. Cases are defined as women with DCIS developing subsequent ipsilateral breast cancer (iIBC), controls as women with DCIS without subsequent iIBC. Multispectral immunohistochemical imaging was performed on primary DCIS lesions, aiming at detection of CD20+ B-cells, CD8+ T-cells, CD3+ T-cells, CD3+Foxp3+ regulatory T-cells, and CD68+ macrophages. Density of immune cell subsets in cells/mm2, immune cell ratios and spatial relationships were calculated for 27 cases and 28 controls. These immune cell related factors were correlated to outcome and integrated with RNAseq data of pure microdissected DCIS. We performed gene set enrichment analysis on the correlation between DCIS gene expression and density of immune cell types with sample permutation (flexgsea R package).

Results: Stromal lymphocyte, B-cell, CD8+ T-cell, regulatory T-cell and macrophage density did not significantly differ between cases and controls. Immune cell composition (CD8+ T-cell/lymphocyte, CD8+ T-cell/CD3+Foxp3+ regulatory T-cell and CD20+/lymphocyte ratio) and fraction of regulatory T-cells in close proximity of a CD8+ T-cell did not differ between cases and controls. We find a negative association between stromal B-cell density and DCIS gene expression of estrogen receptor (ESR1) targets. Higher stromal T-cell density was associated with proliferation and expression of genes characteristic for luminal B and basal-like subtypes. Furthermore, higher density of specific immune cell subsets within the DCIS compartment was associated with several immune and cancer pathways.

Conclusion: A first set of analyzed DCIS cases (n=27) and controls (n=28) show no significant differences regarding immune cell density, composition and spatial relationships. Considering the entire group of DCIS patients (n=55), a negative association between stromal B-cell density and gene expression of ESR1 targets was found. Higher density of lymphocytes was associated with proliferation and expression of genes characteristic for luminal B and basal-like subtypes. The full set of 175 DCIS lesions will be presented at AACR Annual Meeting 2019.

Citation Format: Mathilde M. Almekinders, Lindy Visser, Bram Thijssen, Rianne van der Linden, Charlotte van Rooijen, Petra Kristel, Annegien Broeks, Tycho Bismeijer, Lodewyk Wessels, Erik Hooijberg, Karin de Visser, Esther Lips, Jelle Wesseling, on behalf of the PRECISION team (PREvent ductal Carcinoma In Situ Invasive Overtreatment Now). Progression of ductal carcinoma in situ (DCIS), is it in the immune microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2806.

Absence of integrin α3β1 promotes the progression of HER2-driven breast cancer in vivo

Background

HER2-driven breast cancer is correlated with poor prognosis, especially during its later stages. Numerous studies have shown the importance of the integrin α3β1 during the initiation and progression of breast cancer; however, its role in this disease is complex and often opposite during different stages and in different types of tumors. In this study, we aim to elucidate the role of integrin α3β1 in a genetically engineered mouse model of HER2-driven mammary tumorigenesis.

Methods

To investigate the role of α3β1 in HER2-driven tumorigenesis in vivo, we generated a HER2-driven MMTV-cNeu mouse model of mammary tumorigenesis with targeted deletion of Itga3 (Itga3 KO mice). We have further used several established triple-negative and HER2-overexpressing human mammary carcinoma cell lines and generated ITGA3-knockout cells to investigate the role of α3β1 in vitro. Invasion of cells was assessed using Matrigel- and Matrigel/collagen I-coated Transwell assays under static or interstitial fluid flow conditions. The role of α3β1 in initial adhesion to laminin and collagen was assessed using adhesion assays and immunofluorescence.

Results

Tumor onset in mice was independent of the presence of α3β1. In contrast, the depletion of α3β1 reduced the survival of mice and increased tumor growth and vascularization. Furthermore, Itga3 KO mice were significantly more likely to develop lung metastases and had an increased metastatic burden compared to WT mice. In vitro, the deletion of ITGA3 caused a significant increase in the cellular invasion of HER2-overexpressing SKBR3, AU565, and BT474 cells, but not of triple-negative MDA-MB-231. This invasion suppressing function of α3β1 in HER2-driven cells depended on the composition of the extracellular matrix and the interstitial fluid flow.

Conclusion

Downregulation of α3β1 in a HER2-driven mouse model and in HER2-overexpressing human mammary carcinoma cells promotes progression and invasiveness of tumors. The invasion-suppressive role of α3β1 was not observed in triple-negative mammary carcinoma cells, illustrating the tumor type-specific and complex function of α3β1 in breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1146-8) contains supplementary material, which is available to authorized users.

Validation and clinical application of an LC-MS/MS method for the quantification of everolimus using volumetric absorptive microsampling

Everolimus is a mammalian target of rapamycin inhibitor approved for the treatment of various tumor types. Less invasive measurement of everolimus concentrations could facilitate pharmacokinetic studies and personalized dosing based on whole blood concentrations, known as therapeutic drug monitoring. Volumetric Absorptive Microsampling (VAMS) has been introduced as a patient friendly, less invasive sampling technique to obtain an accurate volume of whole blood regardless of hematocrit value. We describe the bioanalytical validation and clinical application of a liquid chromatography tandem mass spectrometry (LC-MS/MS) method to quantify everolimus using VAMS. For the quantification, ¹³C₂D₄-Everolimus was used as internal standard (IS). Everolimus and the IS were extracted with methanol from the VAMS device, which was evaporated after ultrasonification and shaking. The residue was reconstituted in 20 mM ammonium formate buffer and methanol (50%, v/v) of which 5 μL was injected into the LC-MS/MS system. Quantification was performed for the ammonium adduct of everolimus in positive electrospray ion mode. The VAMS method met all pre-defined validation criteria. Accuracy and precision were within 11.1% and ≤14.6%, respectively. Samples were shown to be stable on the VAMS device for at least 362 days at ambient temperatures. Considerable biases from -20 to 31% were observed over a 30-50% hematocrit range. Although the method fulfilled all validation criteria, the perceived advantage of VAMS over dried blood spot sampling could not be demonstrated. Despite the effect of hematocrit, using an empirically derived formula the whole blood everolimus concentration could be back calculated with reasonable accuracy in the clinical application study.

Abstract 3137: Towards analysis of the immune microenvironment in ductal carcinoma in situ

Introduction

Since the introduction of population-based mammographic screening, the incidence of ductal carcinoma in situ (DCIS) increased manifold. DCIS lesions are non-obligate precursors to invasive breast cancer, because only a minority of DCIS patients later develops invasive breast cancer. DCIS patients are treated intensively with surgery, frequently supplemented by radiotherapy and/or endocrine treatment. However, treatment of DCIS lesions did not result in a decreased incidence of advanced stages of breast cancer, suggesting overdiagnosis and hence overtreatment exists. Because the immune microenvironment plays an important role in cancer progression, we performed a pilot study to assess the amount, composition and spatial distribution of immune cells aiming at the identification of biomarkers that distinguish aggressive from indolent DCIS.

Methods

A representative series of 32 paraffin-embedded DCIS lesions was studied with multispectral immunohistochemical imaging, providing simultaneous detection and quantification of CD20+ B-cells, CD8+ T-cells, CD4+ T-cells, CD4+Foxp3+ regulatory T-cells, CD68+ macrophages and pankeratin. Cellular density of immune cell subsets per tissue compartment and spatial distribution was analyzed by Inform software, SPSS and R. The number of CD4+FoxP3+ T-cells within 30µm of a CD8+ T-cell was assessed and expressed in a CD4+FoxP3+ T-cell per CD8+ T-cell ratio. Immune cell density and composition were correlated to grade and immunohistochemical ER, Her2 and p53 status.

Results

Multispectral immunohistochemical quantification showed a range of 30 to 2100 lymphocytes/mm2 in the stroma of DCIS lesions. High grade positively correlated with higher number of stromal lymphocytes/mm2 (p&lt;0.01). Negative ER status, positive Her2 status and aberrantly expressed p53 was significantly associated with higher number of stromal lymphocytes/mm2, CD8+ T-cells/mm2, CD4+FoxP3+ regulatory T-cells/mm2 and CD20+ B-cells/mm2 (p&lt;0.05). Within the DCIS-epithelium, the number of CD4+FoxP3+ regulatory T-cells positively correlated with negative ER-status (p=0.02) and positive Her2 status (p=0.03). The spatial distribution of the number of CD4+Foxp3+ T-cells within 30 μm of a CD8+ T-cell (expressed in a Treg per CD8+T-cell ratio) varied from 0 to 0.23 in the stromal compartment and from 0 to 0.60 in the DCIS compartment.

Conclusions

Within the immune microenvironment, CD20+ B-cells, CD8+ T-cells, CD4+ T-cells, CD4+Foxp3+ regulatory T-cells and CD68+ macrophages were successfully and simultaneously detected. Stromal lymphocyte density and CD8+ T-cell, CD4+ T-cell, CD4+FoxP3+ regulatory T-cell and CD20+ B-cell density positively correlated with negative ER status, positive Her2 status and aberrant expression of p53. The next step will be to analyze this multiplex panel in our nationwide DCIS cohort (1989-2005, median follow-up 12.0 years) for correlation with clinical outcome.

Citation Format: Mathilde M. Almekinders, Lindy L. Visser, Bram Thijssen, Petra Kristel, Rianne van der Linden, Annegien Broeks, Erik Hooijberg, Karin de Visser, Esther H. Lips, Jelle Wesseling. Towards analysis of the immune microenvironment in ductal carcinoma in situ [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3137.

Integrative Modeling Identifies Key Determinants of Inhibitor Sensitivity in Breast Cancer Cell Lines

Cancer cell lines differ greatly in their sensitivity to anticancer drugs as a result of different oncogenic drivers and drug resistance mechanisms operating in each cell line. Although many of these mechanisms have been discovered, it remains a challenge to understand how they interact to render an individual cell line sensitive or resistant to a particular drug. To better understand this variability, we profiled a panel of 30 breast cancer cell lines in the absence of drugs for their mutations, copy number aberrations, mRNA, protein expression and protein phosphorylation, and for response to seven different kinase inhibitors. We then constructed a knowledge-based, Bayesian computational model that integrates these data types and estimates the relative contribution of various drug sensitivity mechanisms. The resulting model of regulatory signaling explained the majority of the variability observed in drug response. The model also identified cell lines with an unexplained response, and for these we searched for novel explanatory factors. Among others, we found that 4E-BP1 protein expression, and not just the extent of phosphorylation, was a determinant of mTOR inhibitor sensitivity. We validated this finding experimentally and found that overexpression of 4E-BP1 in cell lines that normally possess low levels of this protein is sufficient to increase mTOR inhibitor sensitivity. Taken together, our work demonstrates that combining experimental characterization with integrative modeling can be used to systematically test and extend our understanding of the variability in anticancer drug response.Significance: By estimating how different oncogenic mutations and drug resistance mechanisms affect the response of cancer cells to kinase inhibitors, we can better understand and ultimately predict response to these anticancer drugs.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/15/4396/F1.large.jpg Cancer Res; 78(15); 4396-410. ©2018 AACR.

Bayesian data integration for quantifying the contribution of diverse measurements to parameter estimates

Motivation

Computational models in biology are frequently underdetermined, due to limits in our capacity to measure biological systems. In particular, mechanistic models often contain parameters whose values are not constrained by a single type of measurement. It may be possible to achieve better model determination by combining the information contained in different types of measurements. Bayesian statistics provides a convenient framework for this, allowing a quantification of the reduction in uncertainty with each additional measurement type. We wished to explore whether such integration is feasible and whether it can allow computational models to be more accurately determined.

Results

We created an ordinary differential equation model of cell cycle regulation in budding yeast and integrated data from 13 different studies covering different experimental techniques. We found that for some parameters, a single type of measurement, relative time course mRNA expression, is sufficient to constrain them. Other parameters, however, were only constrained when two types of measurements were combined, namely relative time course and absolute transcript concentration. Comparing the estimates to measurements from three additional, independent studies, we found that the degradation and transcription rates indeed matched the model predictions in order of magnitude. The predicted translation rate was incorrect however, thus revealing a deficiency in the model. Since this parameter was not constrained by any of the measurement types separately, it was only possible to falsify the model when integrating multiple types of measurements. In conclusion, this study shows that integrating multiple measurement types can allow models to be more accurately determined.

Availability and implementation

The models and files required for running the inference are included in the Supplementary information.

Contact

l.wessels@nki.nl.

Supplementary information

Supplementary data are available at Bioinformatics online.

Development and validation of a high-performance liquid chromatography-tandem mass spectrometry assay for the quantification of Dexamphetamine in human plasma

Dexamphetamine is registered for the treatment of attention deficit hyperactivity disorder and narcolepsy. Current research has highlighted the possible application of dexamphetamine in the treatment of cocaine addiction. To support clinical pharmacologic trials a new simple, fast, and sensitive assay for the quantification of dexamphetamine in human plasma using liquid chromatography tandem mass spectrometry (LC-MS/MS) was developed. Additionally, it is the first reported LC-MS assay with these advantages to be fully validated according to current US FDA and EMA guidelines. Human plasma samples were collected on an outpatient basis and stored at nominally -20°C. The analyte and the internal standard (stable isotopically labeled dexamphetamine) were extracted using double liquid-liquid extraction (plasma-organic and organic-water) combined with snap-freezing. The aqueous extract was filtered and 2μL was injected on a C18-column with isocratic elution and analyzed with triple quadrupole mass spectrometry in positive ion mode. The validated concentration range was from 2.5-250ng/mL and the calibration model was linear. A weighting factor of 1 over the squared concentration was applied and correlation coefficients of 0.997 or better were obtained. At all concentrations the bias was within ±15% of the nominal concentrations and imprecision was ≤15%. All results were within the acceptance criteria of the latest US FDA guidance and EMA guidelines on method validation. In conclusion, the developed method to quantify dexamphetamine in human plasma was fit to support a clinical study with slow-release dexamphetamine.

BCM: toolkit for Bayesian analysis of Computational Models using samplers

BACKGROUND

Computational models in biology are characterized by a large degree of uncertainty. This uncertainty can be analyzed with Bayesian statistics, however, the sampling algorithms that are frequently used for calculating Bayesian statistical estimates are computationally demanding, and each algorithm has unique advantages and disadvantages. It is typically unclear, before starting an analysis, which algorithm will perform well on a given computational model.

RESULTS

We present BCM, a toolkit for the Bayesian analysis of Computational Models using samplers. It provides efficient, multithreaded implementations of eleven algorithms for sampling from posterior probability distributions and for calculating marginal likelihoods. BCM includes tools to simplify the process of model specification and scripts for visualizing the results. The flexible architecture allows it to be used on diverse types of biological computational models. In an example inference task using a model of the cell cycle based on ordinary differential equations, BCM is significantly more efficient than existing software packages, allowing more challenging inference problems to be solved.

CONCLUSIONS

BCM represents an efficient one-stop-shop for computational modelers wishing to use sampler-based Bayesian statistics.

Abstract CN05-02: From the cancer landscape to personalized treatment

While many oncogenic drivers and drug resistance mechanisms have been discovered, it is generally unclear how these mechanisms interact to induce sensitivity or resistance in a cell line for a particular drug. To systematically unravel these mechanisms, we developed a combined computational and experimental approach based on high throughput datasets and show these can be employed to predict response to anti-cancer agents. Specifically, we characterized 30 breast cancer cell lines at the DNA, RNA and protein level, and measured the response to various inhibitors. We then constructed Bayesian models encompassing several of the important driver pathways and resistance mechanisms, which we extracted from the literature and knowledge bases. Subsequently we tested how well these models describe the available data. The models provide estimates of the relative contribution of each of the drivers and resistance mechanisms and allow estimation of latent variables such as ‘pathway activation'. We demonstrate the utility of the models by thoroughly analyzing which parts of the data cannot be explained even by fairly extensive models. This provides interesting new leads and narrows down which follow-up studies may be most fruitful to advance our understanding of drug response. The systematic, quantitative understanding of drug response gained from these models will contribute significantly towards precision medicine for individual cancer patients.

Citation Format: Lodewyk Wessels, Bram Thijssen, Kathy Jastrzebski, Roderick Beijersbergen. From the cancer landscape to personalized treatment. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr CN05-02.

Abstract B2-37: Understanding the variability in drug response in a panel of breast cancer cell lines using computational models

Cancer cell lines differ widely in their sensitivity to anticancer drugs. While many oncogenic drivers and drug resistance mechanisms have been discovered, it is generally unclear how these mechanisms interact in each cell line to make the cell line sensitive or resistant to a particular drug.

We set out to explain this variability in drug sensitivity in a panel of 30 breast cancer cell lines. We characterized these cell lines at the DNA, RNA and protein level, and accurately measured the proliferation under treatment with various different kinase inhibitors. We then constructed computational models encompassing several of the important driver pathways and sensitivity mechanisms, and tested how well these models describe the available data. After selecting the well-fitting models, we could use these models to estimate the relative contribution of each of the interacting mechanisms to the proliferation of the cells under drug treatment. For example, the models indicated that FGF2 autocrine signaling contributes to fast proliferation in some cell lines; that SGK1 expression provides a bypass for Akt signaling in some cell lines; or that the expression level of 4E-BP1 is a key determinant of mTOR-inhibitor sensitivity on top of other genetic alterations in the PI3K-pathway. Additionally, we could use these models to thoroughly analyze which parts of the data cannot be explained. This greatly narrows down which follow-up studies are necessary to advance our understanding of drug response.

These results show that knowledge-based computational models can be used to systematically study drug response in cell line panels. Such systematic, quantitative understanding of drug response will be useful in working towards precision medicine for individual cancer patients.

Citation Format: Bram Thijssen, Katarzyna Jastrzebski, Roderick L. Beijersbergen, Lodewyk FA Wessels. Understanding the variability in drug response in a panel of breast cancer cell lines using computational models. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-37.

Target essentiality and centrality characterize drug side effects

To investigate factors contributing to drug side effects, we systematically examine relationships between 4,199 side effects associated with 996 drugs and their 647 human protein targets. We find that it is the number of essential targets, not the number of total targets, that determines the side effects of corresponding drugs. Furthermore, within the context of a three-dimensional interaction network with atomic-resolution interaction interfaces, we find that drugs causing more side effects are also characterized by high degree and betweenness of their targets and highly shared interaction interfaces on these targets. Our findings suggest that both essentiality and centrality of a drug target are key factors contributing to side effects and should be taken into consideration in rational drug design.

The ultimate goal of medical research is to develop effective treatments for disease with minimal side effects. Currently, about 20% of drug candidates failed at clinical trial phases II and III due to safety issues. Therefore, understanding the determining factors of drug side effects is of paramount importance to human health and the pharmaceutical industry. Here, we present the first systematic study to uncover key factors leading to drug side effects within the framework of the human protein interactome network. Our results show that it is the number of essential targets, not the number of total targets, of a drug that determines the occurrence of its side effects. Furthermore, we find that the centrality, both degree and betweenness, of the drug targets is also an important determining factor of drug side effects. Our findings will shed light on new factors to be incorporated into the drug development pipeline.

Temperature dependence of the dielectric permittivity of acetic acid, propionic acid and their methyl esters: a molecular dynamics simulation study

For most liquids, the static relative dielectric permittivity is a decreasing function of temperature, because enhanced thermal motion reduces the ability of the molecular dipoles to orient under the effect of an external electric field. Monocarboxylic fatty acids ranging from acetic to octanoic acid represent an exception to this general rule. Close to room temperature, their dielectric permittivity increases slightly with increasing temperature. Herein, the causes for this anomaly are investigated based on molecular dynamics simulations of acetic and propionic acids at different temperatures in the interval 283-363 K, using the GROMOS 53A6(OXY) force field. The corresponding methyl esters are also considered for comparison. The dielectric permittivity is calculated using either the box-dipole fluctuation (BDF) or the external electric field (EEF) methods. The normal and anomalous temperature dependences of the permittivity for the esters and acids, respectively, are reproduced. Furthermore, in the EEF approach, the response of the acids to an applied field of increasing strength is found to present two successive linear regimes before reaching saturation. The low-field permittivity ε, comparable to that obtained using the BDF approach, increases with increasing temperature. The higher-field permittivity ε' is slightly larger, and decreases with increasing temperature. Further analyses of the simulations in terms of radial distribution functions, hydrogen-bonded structures, and diffusion properties suggest that increasing the temperature or the applied field strength both promote a relative population shift from cyclic (mainly dimeric) to extended (chain-like) hydrogen-bonded structures. The lower effective dipole moment associated with the former structures compared to the latter ones provides an explanation for the peculiar dielectric properties of the two acids compared to their methyl esters.

Development and validation of LC-MS/MS assays for the quantification of E7080 and metabolites in various human biological matrices

To support clinical pharmacokinetic studies with the anticancer agent E7080 (lenvatinib), liquid chromatography tandem mass spectrometry (LC-MS/MS) methods were developed for the quantification of E7080 and four of its metabolites in human plasma, urine and faeces and of E7080 in whole blood. Cross-analyte interferences between metabolites and parent compound were expected and therefore accounted for early in the method development. Plasma, urine and faeces samples were extracted with acetonitrile. Chromatographic separation was achieved on a 50 mm × 2.1 mm I.D. XTerra MS C18 column, with a 0.2 mL/min flow and gradient elution starting with 100% formic acid in water, followed by an increasing percentage of acetonitrile. Whole blood samples were extracted with diethyl ether and extracts were injected on a 150 mm × 2.1mm I.D. Symmetry Shield RP8 column. Detection was performed using an API3000 triple quadrupole mass spectrometer, with a turbo ion spray interface, operating in positive ion mode. Using 250 μL of plasma, E7080 and its metabolites could be quantified between 0.25 and 50.0ng/mL. The quantifiable ranges of E7080 in whole blood, urine and faeces were 0.25-500 ng/mL, 1.00-500 ng/mL and 0.1-25μg/g, using sample volumes of 250 μL, 200 μL and 250 mg, respectively. Calibration curves in all matrices were linear with a correlation coefficient (r(2)) of 0.994 or better. At the lower limit of quantification, accuracies were within ±20% of the nominal concentration with CV values less than 20%. At the other concentrations the accuracies were within ±15% of the nominal concentration with CV values below 15%. The developed methods have successfully been applied in a mass balance study of E7080.

Three-dimensional reconstruction of protein networks provides insight into human genetic disease

To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies.

A novel self-microemulsifying formulation of paclitaxel for oral administration to patients with advanced cancer

To explore the parmacokinetics, safety and tolerability of paclitaxel after oral administration of SMEOF#3, a novel Self-Microemulsifying Oily Formulation, in combination with cyclosporin A (CsA) in patients with advanced cancer. Seven patients were enrolled and randomly assigned to receive oral paclitaxel (SMEOF#3) 160 mg+CsA 700 mg on day 1, followed by oral paclitaxel (Taxol®) 160 mg+CsA 700 mg on day 8 (group I) or vice versa (group II). Patients received paclitaxel (Taxol®) 160 mg as 3-h infusion on day 15. The median (range) area under the plasma concentration–time curve of paclitaxel was 2.06 (1.15–3.47) μg h ml⁻¹ and 1.97 (0.58–3.22) μg h ml⁻¹ after oral administration of SMEOF#3 and Taxol®, respectively, and 4.69 (3.90–6.09) μg h ml⁻¹ after intravenous Taxol®. Oral SMEOF#3 resulted in a lower median T_max of 2.0 (0.5–2.0) h than orally applied Taxol® (T_max=4.0 (0.8–6.1) h, P=0.02). The median apparent bioavailability of paclitaxel was 40 (19–83)% and 55 (9–70)% for the oral SMEOF#3 and oral Taxol® formulation, respectively. Oral paclitaxel administered as SMEOF#3 or Taxol® was safe and well tolerated by the patients. Remarkably, the SMEOF#3 formulation resulted in a significantly lower T_max than orally applied Taxol®, probably due to the excipients in the SMEOF#3 formulation resulting in a higher absorption rate of paclitaxel.