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.

Prognostic impact of HER2 biomarker levels in trastuzumab-treated early HER2-positive breast cancer

BACKGROUND

Overexpression of human epidermal growth factor receptor 2 (HER2) caused by HER2 gene amplification is a driver in breast cancer tumorigenesis. We aimed to investigate the prognostic significance of manual scoring and digital image analysis (DIA) algorithm assessment of HER2 copy numbers and HER2/CEP17 ratios, along with ERBB2 mRNA levels among early-stage HER2-positive breast cancer patients treated with trastuzumab.

METHODS

This retrospective study comprised 371 early HER2-positive breast cancer patients treated with adjuvant trastuzumab, with HER2 re-testing performed on whole tumor sections. Digitized tumor tissue slides were manually scored and assessed with uPath HER2 Dual ISH image analysis, breast algorithm. Targeted ERBB2 mRNA levels were assessed by the Xpert® Breast Cancer STRAT4 Assay. HER2 copy number and HER2/CEP17 ratio from in situ hybridization assessment, along with ERBB2 mRNA levels, were explored in relation to recurrence-free survival (RFS).

RESULTS

The analysis showed that patients with tumors with the highest and lowest manually counted HER2 copy number levels had worse RFS than those with intermediate levels (HR = 2.7, CI 1.4-5.3, p = 0.003 and HR = 2.1, CI 1.1-3.9, p = 0.03, respectively). A similar trend was observed for HER2/CEP17 ratio, and the DIA algorithm confirmed the results. Moreover, patients with tumors with the highest and the lowest values of ERBB2 mRNA had a significantly worse prognosis (HR = 2.7, CI 1.4-5.1, p = 0.003 and HR = 2.8, CI 1.4-5.5, p = 0.004, respectively) compared to those with intermediate levels.

CONCLUSIONS

Our findings suggest that the association between any of the three HER2 biomarkers and RFS was nonlinear. Patients with tumors with the highest levels of HER2 gene amplification or ERBB2 mRNA were associated with a worse prognosis than those with intermediate levels, which is of importance to investigate in future clinical trials studying HER2-targeted therapy.

MYC as a driver of stochastic chromatin networks: implications for the fitness of cancer cells

The relationship between stochastic transcriptional bursts and dynamic 3D chromatin states is not well understood. Using an innovated, ultra-sensitive technique, we address here enigmatic features underlying the communications between MYC and its enhancers in relation to the transcriptional process. MYC thus interacts with its flanking enhancers in a mutually exclusive manner documenting that enhancer hubs impinging on MYC detected in large cell populations likely do not exist in single cells. Dynamic encounters with pathologically activated enhancers responsive to a range of environmental cues, involved <10% of active MYC alleles at any given time in colon cancer cells. Being the most central node of the chromatin network, MYC itself likely drives its communications with flanking enhancers, rather than vice versa. We submit that these features underlie an acquired ability of MYC to become dynamically activated in response to a diverse range of environmental cues encountered by the cell during the neoplastic process.

PD-1 protein and gene expression in early breast cancer: Prognostic implications

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Background: We have previously shown the prognostic value of PD-L1 protein and gene expression in early breast cancer (BC), however, the prognostic role of PD-1 expression remains unclear. Methods: The prognostic value of PD-1 in early BC was investigated using three different approaches: i) evaluation of PD-1 at the protein (IHC, immunohistochemistry in tissue microarrays) and mRNA levels in a retrospective patient cohort of 586 patients treated for early BC in Stockholm, Sweden between 1997-2005, ii) systematic review and trial-level meta-analysis of studies published in Medline, Embase, Cochrane Library and Web of Science Core Collection libraries on the prognostic value of PD-1 IHC expression, and iii) pooled analysis of transcriptomic data from 39 publicly available datasets for the prognostic capacity of PD-1 gene expression. Univariate and multivariable Cox regression models were used. Results: In the retrospective study cohort, PD-1 protein was significantly associated with biologically high-risk characteristics. PD-1 protein, but not gene expression, was correlated with improved overall survival (OS) (adjusted HR = 0.73, 95% CI 0.55 – 0.96, p = 0.023 and adjusted HR = 0.88, 95% CI 0.68 – 1.13, p = 0.307, respectively). In the trial-level meta-analysis, 4736 entries were initially identified and 15 studies, including our original cohort, fulfilled the predefined eligibility criteria. PD-1 IHC expression was not prognostic in unselected patients. However, a significant correlation to improved disease-free survival was seen within the triple-negative subtype (pooled multivariate HR = 0.57, 95% CI 0.29 – 0.90, p = 0.02). In the pooled gene expression analysis, PD-1 gene expression was associated with improved OS in the entire population (adjusted HR = 0.89, 95% CI 0.80 – 0.99, p = 0.025) and in basal-like (adjusted HR = 0.77, 95% CI 0.63 – 0.95, p = 0.014) tumors. Conclusions: PD-1 expression at the RNA and protein levels represent promising prognostic factors, especially in the triple-negative and basal-like subtypes. Standardization and further validation are needed prior to clinical implementation.

Programmed death-ligand 1 gene expression is a prognostic marker in early breast cancer and provides additional prognostic value to 21-gene and 70-gene signatures in estrogen receptor-positive disease

Gene and protein expression of programmed death‐ligand 1 (PD‐L1) are prognostic in early breast cancer (BC), but their prognostic information is inconsistent at least in some biological subgroups. The validated prognostic gene signatures (GS) in BC are mainly based on proliferation and estrogen receptor (ER)‐related genes. Here, we aimed to explore the prognostic capacity of PD‐L1 expression at the protein vs mRNA levels and to investigate the prognostic information that PD‐L1 can potentially add to routinely used GS. Gene expression data were derived from two early BC cohorts (cohort 1: 562 patients; cohort 2: 1081 patients). Tissue microarrays from cohort 1 were immunohistochemically (IHC) stained for PD‐L1 using the SP263 clone. GS scores (21‐gene, 70‐gene) were calculated, and likelihood‐ratio (LR) tests and concordance indices were used to evaluate the additional prognostic information for each signature. The immune cell composition was also evaluated using the CIBERSORT in silico tool. PD‐L1 gene and protein expressions were independently associated with better prognosis. In ER+/HER2− patients, PD‐L1 gene expression provided significant additional prognostic information beyond that of both 21‐GS [LR‐Δχ² = 15.289 and LR‐Δχ² = 8.812, P < 0.01 for distant metastasis‐free interval (DMFI) in cohorts 1 and 2, respectively] and 70‐GS score alone (LR‐Δχ² = 18.198 and LR‐Δχ² = 8.467, P < 0.01 for DMFI in cohorts 1 and 2, respectively). PD‐L1 expression was correlated with IHC‐determined CD3+ cells (r = 0.41, P < 0.001) and with CD8+ (r = 0.62, P < 0.001) and CD4+ memory activated (r = 0.66, P < 0.001) but not with memory resting (r = −0.063, P = 0.14) or regulatory (r = −0.12, P < 0.01) T cells in silico. PD‐L1 gene expression represents a promising favorable prognostic marker and can provide additional prognostic value to 21‐ and 70‐gene scores in ER+/HER2− BC.

STAT3 Activity Promotes Programmed-Death Ligand 1 Expression and Suppresses Immune Responses in Breast Cancer

Signal transducer and activator of transcription 3 (STAT3) is an oncogene and multifaceted transcription factor involved in multiple cellular functions. Its role in modifying anti-tumor immunity has been recently recognized. In this study, the biologic effects of STAT3 on immune checkpoint expression and anti-tumor responses were investigated in breast cancer (BC). A transcriptional signature of phosphorylated STAT3 was positively correlated with PD-L1 expression in two independent cohorts of early BC. Pharmacologic inhibition and gene silencing of STAT3 led to decreased Programmed Death Ligand 1 (PD-L1) expression levels in vitro, and resulted as well in reduction of tumor growth and decreased metastatic dissemination in a mammary carcinoma mouse model. The hampering of tumor progression was correlated to an anti-tumoral macrophage phenotype and accumulation of natural-killer cells, but also in reduced accrual of cytotoxic lymphocytes. In human BC, pro-tumoral macrophages correlated to PD-L1 expression, proliferation status and higher grade of malignancy, indicating a subset of patients with immunosuppressive properties. In conclusion, this study provides evidence for STAT3-mediated regulation of PD-L1 and modulation of immune microenvironment in BC.

Prognostic value of PD-L1 gene expression with Recurrence Score and 70-gene signature in patients with ER+/HER2- early breast cancer

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Background: We have previously demonstrated that PD-L1 mRNA expression can serve as prognostic biomarker in breast cancer (BC). In ER+/HER2- BC, RS and 70-gene signature are used to predict the risk of recurrence and benefit from chemotherapy. Methods: Discovery cohort (cohort 1) included 302 patients diagnosed with primary ER+/HER2- BC (1997-2005) in Stockholm health care region. Gene expression profiling has been performed using DNA microarrays (GSE48091) while information regarding tumor characteristics, treatment and follow-up have been obtained. TCGA’s dataset including 590 ER+/HER2- patients, was used as validation cohort (cohort 2). Kaplan–Meier estimates and Cox regression univariate/multivariable analyses were performed using breast cancer-specific survival(BCSS) and progression-free interval (PFI) as endpoints in cohorts 1 and 2, respectively. Gene signature scores were calculated using the R genefu package. Likelihood ratio (LR) tests and concordance indices (c-indices) were used to assess each score’s added prognostic value. Results: PD-L1 mRNA expression (treated as a continuous variable) was independently associated with better BCSS in cohort 1 (HR = 0.72; 95% CI = 0.58-0.90;p = 0.003) and with better PFI in cohort 2 (HR = 0.67; 95% CI = 0.50-0.90; p = 0.008) in the multivariable analysis. PD-L1 provided significant additional prognostic information beyond that of both RS alone (LR-Δχ2= 9.6; p = 0.002 and LR-Δχ2= 9.7; p = 0.002, in cohorts 1 and 2, respectively), and 70-gene signature score alone (LR-Δχ2= 10.4; p = 0.001 and LR-Δχ2= 9.2; p = 0.002 in cohort 1 and 2, respectively). C-indices for PD-L1 + RS vs RS were 0.65 vs 0.60 (cohort 1) and 0.66 vs 0.60 (cohort 2), and for PD-L1 + 70-gene vs 70-gene were 0.65 vs 0.59 (cohort 1) and 0.64 vs 0.54 (cohort 2), respectively. Conclusions: PD-L1 gene expression was correlated with better outcomes and can provide added prognostic value to RS and 70-gene signature scores in ER+/HER2- BC.

A composite framework for the statistical analysis of epidemiological DNA methylation data with the Infinium Human Methylation 450K BeadChip

High-throughput DNA methylation profiling exploits microarray technologies thus providing a wealth of data, which however solicits rigorous, generic, and analytical pipelines for an efficient systems level analysis and interpretation. In this study, we utilize the Illumina's Infinium Human Methylation 450K BeadChip platform in an epidemiological cohort, targeting to associate interesting methylation patterns with breast cancer predisposition. The computational framework proposed here extends the--established in transcriptomic microarrays--logarithmic ratio of the methylated versus the unmethylated signal intensities, quoted as M-value. Moreover, intensity-based correction of the M-signal distribution is introduced in order to correct for batch effects and probe-specific errors in intensity measurements. This is accomplished through the estimation of intensity-related error measures from quality control samples included in each chip. Moreover, robust statistical measures exploiting the coefficient variation of DNA methylation measurements between control and case samples alleviate the impact of technical variation. The results presented here are juxtaposed to those derived by applying classical preprocessing and statistical selection methodologies. Overall, in comparison to traditional approaches, the superior performance of the proposed framework in terms of technical bias correction, along with its generic character, support its suitability for various microarray technologies.

Robust carotid artery recognition in longitudinal B-mode ultrasound images

Automatic segmentation of the arterial lumen from ultrasound images is an important task in clinical diagnosis. Carotid artery recognition, the first task in lumen segmentation, should be performed in a fully automated, fast, and reliable way to further facilitate the low-level task of arterial delineation. In this paper, a user-independent, real-time algorithm is introduced for carotid artery localization in longitudinal B-mode ultrasound images. The proposed technique acts directly on the raw image, and exploits basic statistics along with anatomical knowledge. The method's evaluation and parameter value optimization were performed on a threefold cross validation basis. In addition, the introduced algorithm was systematically compared with another algorithm for common carotid artery recognition in B-mode scans, separately for multi-frame and single-frame data. The data sets used included 2,149 images from 100 subjects taken from three different institutions and covering a wide range of possible lumen and surrounding tissue representations. Using the optimized values, the carotid artery was recognized in all the processed images in both multi-frame and single-frame data. Thus, the introduced technique will further reinforce automatic segmentation in longitudinal B-mode ultrasound images.

Elucidating the identity of resistance mechanisms to prednisolone exposure in acute lymphoblastic leukemia cells through transcriptomic analysis: A computational approach

Background

It has been shown previously that glucocorticoids exert a dual mechanism of action, entailing cytotoxic, mitogenic as well as cell proliferative and anti-apoptotic responses, in a dose-dependent manner on CCRF-CEM cells at 72 h. Early gene expression response implies a dose-dependent dual mechanism of action of prednisolone too, something reflected on cell state upon 72 h of treatment.

Methods

In this work, a generic, computational microarray data analysis framework is proposed, in order to examine the hypothesis, whether CCRF-CEM cells exhibit an intrinsic or acquired mechanism of resistance and investigate the molecular imprint of this, upon prednisolone treatment. The experimental design enables the examination of both the dose (0 nM, 10 nM, 22 uM, 700 uM) effect of glucocorticoid exposure and the dynamics (early and late, namely 4 h, 72 h) of the molecular response of the cells at the transcriptomic layer.

Results

In this work, we demonstrated that CCRF-CEM cells may attain a mixed mechanism of response to glucocorticoids, however, with a clear preference towards an intrinsic mechanism of resistance. Specifically, at 4 h, prednisolone appeared to down-regulate apoptotic genes. Also, low and high prednisolone concentrations up-regulates genes related to metabolism and signal-transduction in both time points, thus favoring cell proliferative actions. In addition, regulation of NF-κB-related genes implies an inherent mechanism of resistance through the established link of NF-κB inflammatory role and GC-induced resistance. The analysis framework applied here highlights prednisolone-activated regulatory mechanisms through identification of early responding sets of genes. On the other hand, study of the prolonged exposure to glucocorticoids (72 h exposure) highlights the effect of homeostatic feedback mechanisms of the treated cells.

Conclusions

Overall, it appears that CCRF-CEM cells in this study exhibit a diversified, combined pattern of intrinsic and acquired resistance to prednisolone, with a tendency towards inherent resistant characteristics, through activation of different molecular courses of action.

Evaluating the effect of various background correction methods regarding noise reduction, in two-channel microarray data

In this work, two novel background correction (BC) methods, along with several commonly used ones, are evaluated regarding noise reduction in eleven two-channel self-versus-self (SVS) hybridizations. The evaluation of each BC method is investigated under the use of four statistical criteria combined into a single measure, the polygon area measure. Overall, our proposed BC approaches perform very well in terms of the proposed measure for most of the cases and provide an improved effect regarding technical noise reduction.

Using the Hough transform to segment ultrasound images of longitudinal and transverse sections of the carotid artery

Automatic segmentation of the arterial lumen from ultrasound images is an important task in clinical diagnosis. In this paper, the Hough transform (HT) was used to automatically extract straight lines and circles from sequences of B-mode ultrasound images of longitudinal and transverse sections, respectively, of the carotid artery. In 10 normal subjects, the specificity and accuracy of HT-based segmentation were on average higher than 0.96 for both sections, whereas the sensitivity was higher than 0.96 in longitudinal and higher than 0.82 in transverse sections. The intima-media thickness (IMT) was also estimated from images of longitudinal sections; the corresponding validation parameters were generally higher than 0.90. To further validate the results, arterial distension waveforms (ADW) were estimated from sequences of images using the HT technique as well as motion analysis using block matching (BM). In longitudinal sections, diastolic and systolic diameters and relative diameter changes using HT and BM were not significantly different. In transverse sections, diastolic and systolic diameters were significantly lower using the HT technique; the differences were <7%. Relative diameter changes in transverse sections were not significantly different from BM-estimated ones. The HT technique was also applied to four subjects with atherosclerosis, in which sensitivity, specificity and accuracy were comparable to those of normal subjects; the low values of sensitivity in transverse sections may reflect departure from the circular model because of the presence of plaque. In conclusion, the HT technique provides a reliable way to segment ultrasound images of the carotid artery and can be used in clinical practice to estimate indices of arterial wall physiology, such as the IMT and the ADW.