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.

Clinically relevant gene signatures provide independent prognostic information in older breast cancer patients.

BACKGROUND: The clinical utility of gene signatures in older breast cancer patients remains unclear. We aimed to determine signature prognostic capacity in this patient subgroup. METHODS: Research versions of the genomic grade index (GGI), 70-gene, recurrence score (RS), cell cycle score (CCS), PAM50 risk-of-recurrence proliferation (ROR-P), and PAM50 signatures were applied to 39 breast cancer datasets (N = 9583). After filtering on age ≥ 70 years, and the presence of estrogen receptor (ER) and survival data, 871 patients remained. Signature prognostic capacity was tested in all (n = 871), ER-positive/lymph node-positive (ER + /LN + , n = 335) and ER-positive/lymph node-negative (ER + /LN-, n = 374) patients using Kaplan-Meier and multivariable Cox-proportional hazard (PH) modelling. RESULTS: All signatures were statistically significant in Kaplan-Meier analysis of all patients (Log-rank P < 0.001). This significance remained in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN + patients all signatures except PAM50 were significant in Kaplan-Meier analysis (Log-rank P ≤ 0.05) and remained so in multivariable analysis (Cox-PH, P ≤ 0.05). In ER + /LN- patients all except RS were significant in Kaplan-Meier analysis (Log-rank P ≤ 0.05) but only the 70-gene, CCS, ROR-P, and PAM50 signatures remained so in multivariable analysis (Cox-PH, P ≤ 0.05). CONCLUSIONS: We found that gene signatures provide prognostic information in survival analyses of all, ER + /LN + and ER + /LN- older (≥ 70 years) breast cancer patients, suggesting a potential role in aiding treatment decisions in older patients.

Gonadotropin Releasing Hormone agonist (GnRHa) during chemotherapy and post-cancer childbirths - a Nationwide population-based cohort study of 24,922 women diagnosed with cancer in Sweden.

Background: Worldwide, an increasing number of women with cancer are receiving Gonadotropin Releasing Hormone agonist (GnRHa) co-treatment during chemotherapy aiming at ovarian protection. There is divergence among guidelines, and some have recommended GnRHa co-treatment for women with breast cancer, however, the effect of GnRHa on future fertility is uncertain. Methods: In this population-based cohort study we included all women diagnosed with cancer at ages 15-45 between July 2005 and March 2017 in Sweden, identified in the Swedish Cancer Register. Exposure to GnRHa co-treatment was captured using the Prescribed Drug Register. Post-cancer childbirth, extracted from the Medical Birth Register, was the main outcome. Secondary outcomes included childbirths achieved through natural conception (NC), infertility diagnosis and cancer mortality. For each outcome, adjusted hazard ratios (aHR) and 95% confidence intervals (CI) were estimated using delayed-entry Cox models, stratified by age and cancer site. Findings: Among 24,922 women diagnosed with cancer, 1.5% had GnRHa co-treatment. Breast cancer diagnoses were found in 80.2% of GnRHa exposed women and the GnRHa exposure was not associated with higher rates of childbirth (aHR 1.23, 95% CI 0.80-1.89), or NC childbirth (aHR 1.02, 95% CI 0.62-1.67), whereas the rate of infertility was significantly higher (aHR 2.42, 95% CI 1.44-4.08). In women with lymphoma and other cancers, GnRHa exposure was not associated with higher rates of childbirth, NC childbirth or infertility. GnRHa exposure was not associated with higher cancer mortality for any cancer type. Interpretation: We did not find evidence of improved or maintained fertility, estimated as childbirth rates post-cancer, in women who received GnRHa during cancer treatment. Funding: This study was financed by research grants from The Swedish Cancer Society (CAN 2017/704; 190249Pj, 200170F), The Swedish Research Council (Dnr 2019-00446), the Nordic Cancer Union NCU (Grant 2017), The Swedish Childhood Cancer Fund (KP2016-0031), Radiumhemmets Forskningsfonder (Dnr: 201313), Stockholm County Council (FoUI-953912) and Karolinska Institutet (Dnr 2020-01963).

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.

The role of serum thymidine kinase 1 activity in neoadjuvant-treated HER2-positive breast cancer: biomarker analysis from the Swedish phase II randomized PREDIX HER2 trial.

BACKGROUND: Thymidine kinase 1 (TK1) plays a pivotal role in DNA synthesis and cellular proliferation. TK1 has been studied as a prognostic marker and as an early indicator of treatment response in human epidermal growth factor 2 (HER2)-negative early and metastatic breast cancer (BC). However, the prognostic and predictive value of serial TK1 activity in HER2-positive BC remains unknown. METHODS: In the PREDIX HER2 trial, 197 HER2-positive BC patients were randomized to neoadjuvant trastuzumab, pertuzumab, and docetaxel (DPH) or trastuzumab emtansine (T-DM1), followed by surgery and adjuvant epirubicin and cyclophosphamide. Serum samples were prospectively collected from all participants at multiple timepoints: at baseline, after cycle 1, 2, 4, and 6, at end of adjuvant therapy, annually for a total period of 5 years and/or at the time of recurrence. The associations of sTK1 activity with baseline characteristics, pathologic complete response (pCR), event-free survival (EFS), and disease-free survival (DFS) were evaluated. RESULTS: No association was detected between baseline sTK1 levels and all the baseline clinicopathologic characteristics. An increase of TK1 activity from baseline to cycle 2 was seen in all cases. sTK1 level at baseline, after 2 and 4 cycles was not associated with pCR status. After a median follow-up of 58 months, 23 patients had EFS events. There was no significant effect between baseline or cycle 2 sTK1 activity and time to event. A non-significant trend was noted among patents with residual disease (non-pCR) and high sTK1 activity at the end of treatment visit, indicating a potentially worse long-term prognosis. CONCLUSION: sTK1 activity increased following neoadjuvant therapy for HER2-positive BC but was not associated with patient outcomes or treatment benefit. However, the post-surgery prognostic value in patients that have not attained pCR warrants further investigation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02568839. Registered on 6 October 2015.

Identification of a Notch transcriptomic signature for breast cancer.

BACKGROUND: Dysregulated Notch signalling contributes to breast cancer development and progression, but validated tools to measure the level of Notch signalling in breast cancer subtypes and in response to systemic therapy are largely lacking. A transcriptomic signature of Notch signalling would be warranted, for example to monitor the effects of future Notch-targeting therapies and to learn whether altered Notch signalling is an off-target effect of current breast cancer therapies. In this report, we have established such a classifier. METHODS: To generate the signature, we first identified Notch-regulated genes from six basal-like breast cancer cell lines subjected to elevated or reduced Notch signalling by culturing on immobilized Notch ligand Jagged1 or blockade of Notch by γ-secretase inhibitors, respectively. From this cadre of Notch-regulated genes, we developed candidate transcriptomic signatures that were trained on a breast cancer patient dataset (the TCGA-BRCA cohort) and a broader breast cancer cell line cohort and sought to validate in independent datasets. RESULTS: An optimal 20-gene transcriptomic signature was selected. We validated the signature on two independent patient datasets (METABRIC and Oslo2), and it showed an improved coherence score and tumour specificity compared with previously published signatures. Furthermore, the signature score was particularly high for basal-like breast cancer, indicating an enhanced level of Notch signalling in this subtype. The signature score was increased after neoadjuvant treatment in the PROMIX and BEAUTY patient cohorts, and a lower signature score generally correlated with better clinical outcome. CONCLUSIONS: The 20-gene transcriptional signature will be a valuable tool to evaluate the response of future Notch-targeting therapies for breast cancer, to learn about potential effects on Notch signalling from conventional breast cancer therapies and to better stratify patients for therapy considerations.

Multiresolution Self-Supervised Feature Integration via Attention Multiple Instance Learning for Histopathology Analysis.

Digital histopathology image analysis of tumor tissue sections has seen great research interest for automating standard diagnostic tasks, but also for developing novel prognostic biomarkers. However, research has mainly been focused on developing uniresolution models, capturing either high-resolution cellular features or low-resolution tissue architectural features. In addition, in the patch-based weakly-supervised training of deep learning models, the features which represent the intratumoral heterogeneity are lost. In this study, we propose a multiresolution attention-based multiple instance learning framework that can capture cellular and contextual features from the whole tissue for predicting patient-level outcomes. Several basic mathematical operations were examined for integrating multiresolution features, i.e. addition, mean, multiplication and concatenation. The proposed multiplication-based multiresolution model performed the best (AUC=0.864), while all multiresolution models outperformed the uniresolution baseline models (AUC=0.669, 0.713) for breast-cancer grading. (Implementation: https://github.com/tsikup/multiresolution-clam).

ProFertil study protocol for the investigation of gonadotropin-releasing hormone agonists (GnRHa) during chemotherapy aiming at fertility protection of young women and teenagers with cancer in Sweden-a phase III randomised double-blinded placebo-controlled study.

BACKGROUND: Gonadotropin-releasing hormone agonists (GnRHa) cotreatment used to transiently suppress ovarian function during chemotherapy to prevent ovarian damage and preserve female fertility is used globally but efficacy is debated. Most clinical studies investigating a beneficial effect of GnRHa cotreatment on ovarian function have been small, retrospective and uncontrolled. Unblinded randomised studies on women with breast cancer have suggested a beneficial effect, but results are mixed with lack of evidence of improvement in markers of ovarian reserve. Unblinded randomised studies of women with lymphoma have not shown any benefit regarding fertility markers after long-term follow-up and no placebo-controlled study has been conducted so far. The aim of this study is to investigate if administration of GnRHa during cancer treatment can preserve fertility in young female cancer patients in a double-blind, placebo-controlled clinical trial. METHODS AND ANALYSIS: A prospective, randomised, double-blinded, placebo-controlled, phase III study including 300 subjects with breast cancer. In addition, 200 subjects with lymphoma, acute leukemias and sarcomas will be recruited. Women aged 14-42 will be randomised 1:1 to treatment with GnRHa (triptorelin) or placebo for the duration of their gonadotoxic chemotherapy. Follow-up until 5 years from end of treatment (EoT). The primary endpoint will be change in anti-Müllerian hormone (AMH) recovery at follow-up 12 months after EoT, relative to AMH levels at EoT, comparing the GnRHa group and the placebo group in women with breast cancer. ETHICS AND DISSEMINATION: This study is designed in accordance with the principles of Good Clinical Practice (ICH-GCP E6 (R2)), local regulations (ie, European Directive 2001/20/EC) and the ethical principles of the Declaration of Helsinki. Within 6 months of study completion, the results will be analysed and the study results shall be reported in the EudraCT database. STUDY REGISTRATION: The National Institutional review board in Sweden dnr:2021-03379, approval date 12 October 2021 (approved amendments 12 June 2022, dnr:2022-02924-02 and 13 December 2022, dnr:2022-05565-02). The Swedish Medical Product Agency 19 January 2022, Dnr:5.1-2021-98927 (approved amendment 4 February 2022). Manufacturing authorisation for authorised medicinal products approved 6 December 2021, Dnr:6.2.1-2020-079580. Stockholm Medical Biobank approved 22 June 2022, RBC dnr:202 253. TRIAL REGISTRATION NUMBER: NCT05328258; EudraCT number:2020-004780-71.

FXYD3 functionally demarcates an ancestral breast cancer stem cell subpopulation with features of drug-tolerant persisters.

The heterogeneity of cancer stem cells (CSCs) within tumors presents a challenge in therapeutic targeting. To decipher the cellular plasticity that fuels phenotypic heterogeneity, we undertook single-cell transcriptomics analysis in triple-negative breast cancer (TNBC) to identify subpopulations in CSCs. We found a subpopulation of CSCs with ancestral features that is marked by FXYD domain-containing ion transport regulator 3 (FXYD3), a component of the Na+/K+ pump. Accordingly, FXYD3+ CSCs evolve and proliferate, while displaying traits of alveolar progenitors that are normally induced during pregnancy. Clinically, FXYD3+ CSCs were persistent during neoadjuvant chemotherapy, hence linking them to drug-tolerant persisters (DTPs) and identifying them as crucial therapeutic targets. Importantly, FXYD3+ CSCs were sensitive to senolytic Na+/K+ pump inhibitors, such as cardiac glycosides. Together, our data indicate that FXYD3+ CSCs with ancestral features are drivers of plasticity and chemoresistance in TNBC. Targeting the Na+/K+ pump could be an effective strategy to eliminate CSCs with ancestral and DTP features that could improve TNBC prognosis.

The ever-expanding landscape of antibody-drug conjugates (ADCs) in solid tumors: A systematic review.

BACKGROUND: The advent of targeted therapies signaled novel avenues for more optimal oncological outcomes. Antibody-drug conjugates (ADCs) have risen as a cornerstone of the ever-expanding targeted therapy era. The purpose of this systematic review is to delineate the rapidly evolving clinical landscape of ADCs for solid tumors. METHODS: A literature search was performed in Medline, Embase and Cochrane databases for phase II and III clinical trials. Outcomes of interest were the objective response rate, overall survival, progression-free survival and adverse events. RESULTS: A total of 92 clinical trials (76 phase II and 16 phase III) evaluated the efficacy and safety of ADCs for a plethora of solid tumors. Out of the 30 investigated ADCs, 8 have received approval by regulatory organizations for solid tumors. Currently, 52 phase III clinical trials for ADCs are ongoing. CONCLUSION: ADCs have shown promising results for several solid tumors and various cancer settings.

Impact of BMI in Patients With Early Hormone Receptor-Positive Breast Cancer Receiving Endocrine Therapy With or Without Palbociclib in the PALLAS Trial.

PURPOSE: BMI affects breast cancer risk and prognosis. In contrast to cytotoxic chemotherapy, CDK4/6 inhibitors are given at a fixed dose, irrespective of BMI or weight. This preplanned analysis of the global randomized PALLAS trial investigates the impact of BMI on the side-effect profile, treatment adherence, and efficacy of palbociclib. METHODS: Patients were categorized at baseline according to WHO BMI categories. Neutropenia rates were assessed with univariable and multivariable logistic regression. Time to early discontinuation of palbociclib was analyzed with Fine and Gray competing risk models. Unstratified Cox models were used to investigate the association between BMI category and time to invasive disease-free survival (iDFS). 95% CIs were derived. RESULTS: Of 5,698 patients included in this analysis, 68 (1.2%) were underweight, 2,082 (36.5%) normal weight, 1,818 (31.9%) overweight, and 1,730 (30.4%) obese at baseline. In the palbociclib arm, higher BMI was associated with a significant decrease in neutropenia (unadjusted odds ratio for 1-unit change, 0.93; 95% CI, 0.91 to 0.94; adjusted for age, race ethnicity, region, chemotherapy use, and Eastern Cooperative Oncology Group at baseline, 0.93; 95% CI, 0.92 to 0.95). This translated into a significant decrease in treatment discontinuation rate with higher BMI (adjusted hazard ratio [HR] for 10-unit change, 0.75; 95% CI, 0.67 to 0.83). There was no significant improvement in iDFS with the addition of palbociclib to ET in any weight category (normal weight HR, 0.84; 95% CI, 0.63 to 1.12; overweight HR, 1.10; 95% CI, 0.82 to 1.49; and obese HR, 0.95; 95% CI, 0.69 to 1.30) in this analysis early in follow-up (31 months). CONCLUSION: This preplanned analysis of the PALLAS trial demonstrates a significant impact of BMI on side effects, dose reductions, early treatment discontinuation, and relative dose intensity. Additional long-term follow-up will further evaluate whether BMI ultimately affects outcome.

The interplay between eosinophils and T cells in breast cancer immunotherapy.

Treatment with immune checkpoint inhibitors (ICI) has revolutionized cancer management for multiple tumor types, including breast cancer. However, not all patients respond to ICI, and unraveling the determinants and mechanisms of response still remains an unmet need. A recent study has uncovered the critical role of eosinophils in mediating immunotherapy effect in breast cancer, mainly by stimulating the activation of CD8+ T-cells. Furthermore, the intratumoral eosinophil recruitment was directed by CD4+ T cells and the interleukins IL-5 and IL-33, thus providing the rationale for targeting eosinophils to enhance ICI response.

Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial.

PURPOSE: PREDIX HER2 is a randomized Phase II trial that compared neoadjuvant docetaxel, trastuzumab, and pertuzumab (THP) with trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Rates of pathologic complete response (pCR) did not differ between the two groups. Here, we present the survival outcomes from PREDIX HER2 and investigate metabolic response and tumor-infiltrating lymphocytes (TIL) as prognostic factors. PATIENTS AND METHODS: In total, 202 patients with HER2-positive breast cancer were enrolled and 197 patients received six cycles of either THP or T-DM1. Secondary endpoints included event-free survival (EFS), recurrence-free survival (RFS), and overall survival (OS). Assessment with PET/CT was performed at baseline, after two and six treatment cycles. TILs were assessed manually at baseline biopsies, while image-based evaluation of TILs [digital TILs (DTIL)] was performed in digitized full-face sections. RESULTS: After a median follow-up of 5.21 years, there was no difference between the two treatment groups in terms of EFS [HR = 1.26; 95% confidence interval (CI), 0.54-2.91], RFS (HR = 0.69; 95% CI, 0.24-1.93), or OS (HR = 0.52; 95% CI, 0.09-2.82). Higher SUVmax at cycle 2 (C2) predicted lower pCR (ORadj = 0.65; 95% CI, 0.48-0.87; P = 0.005) and worse EFS (HRadj = 1.27; 95% CI, 1.12-1.41; P < 0.001). Baseline TILs and DTILs provided additional prognostic information to clinical parameters and C2 SUVmax. CONCLUSIONS: Long-term outcomes following neoadjuvant T-DM1 were similar to neoadjuvant THP. SUVmax after two cycles of neoadjuvant therapy for HER2-positive breast cancer may be an independent predictor of both short- and long-term outcomes. Combined assessment with TILs may facilitate early selection of poor responders for alternative treatment strategies.

Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.

Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

Expression patterns and prognostic implications of tumor-infiltrating lymphocytes dynamics in early breast cancer patients receiving neoadjuvant therapy: A systematic review and meta-analysis.

Purpose: High levels of tumor-infiltrating lymphocytes (TILs) are associated with better outcomes in early breast cancer and higher pathological response rates to neoadjuvant chemotherapy especially in the triple-negative (TNBC) and HER2+ subtypes. However, the dynamic changes in TILs levels after neoadjuvant treatment (NAT) are less studied. This systematic review and meta-analysis aimed to investigate the patterns and role of TILs dynamics change in early breast cancer patients receiving NAT. Methods: Medline, Embase, Web of Science Core Collection and PubMed Central databases were searched for eligible studies. Data were extracted independently by two researchers and discordances were resolved by a third. Pooled TILs rates pre- & post-treatment (overall and per subtype), pooled rates of ΔTILs and direction of change after NAT as well as correlation of ΔTILs with survival outcomes were generated in the outcome analysis. Results: Of 2116 identified entries, 34 studies fulfilled the criteria and provided adequate data for the outcomes of interest. A decreased level of TILs was observed after NAT in paired samples across all subtypes. The effect of NAT on TILs was most prominent in TNBC subtype with a substantial change, either increase or decrease, in 79.3% (95% CI 61.7-92.6%) of the patients as well as in HER2+ disease (14.4% increased vs 46.2% decreased). An increase in ΔTILs in TNBC was associated with better disease-free/relapse-free survival in pooled analysis (univariate HR = 0.59, 95% CI: 0.37-0.95, p = 0.03). Conclusion: This meta-analysis illustrates the TILs dynamics during NAT for breast cancer and indicates prognostic implications of ΔTILs in TNBC. The potential clinical utility of the longitudinal assessment of TILs during neoadjuvant therapy warrants further validation.

Harmonization Strategies in Multicenter MRI-Based Radiomics.

Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient information directly from images that are decoded into handcrafted features, comprising descriptors of shape, size and textural patterns. Although radiomics is gaining momentum since it holds great promise for accelerating digital diagnostics, it is susceptible to bias and variation due to numerous inter-patient factors (e.g., patient age and gender) as well as inter-scanner ones (different protocol acquisition depending on the scanner center). A variety of image and feature based harmonization methods has been developed to compensate for these effects; however, to the best of our knowledge, none of these techniques has been established as the most effective in the analysis pipeline so far. To this end, this review provides an overview of the challenges in optimizing radiomics analysis, and a concise summary of the most relevant harmonization techniques, aiming to provide a thorough guide to the radiomics harmonization process.

Real World Evaluation of the Prosigna/PAM50 Test in a Node-Negative Postmenopausal Swedish Population: A Multicenter Study.

Molecular signatures to guide decisions for adjuvant chemotherapy are recommended in early ER-positive, HER2-negative breast cancer. The objective of this study was to assess what impact gene-expression-based risk testing has had following its recommendation by Swedish national guidelines. Postmenopausal women with ER-positive, HER2-negative and node negative breast cancer at intermediate clinical risk and eligible for chemotherapy were identified retrospectively from five Swedish hospitals. Tumor characteristics, results from Prosigna® test and final treatment decision were available for all patients. Treatment recommendations were compared with the last version of regional guidelines before the introduction of routine risk signature testing. Among the 360 included patients, 41% (n = 148) had a change in decision for adjuvant treatment based on Prosigna® test result. Out of the patients with clinical indication for adjuvant chemotherapy, 52% (n = 118) could avoid treatment based on results from Prosigna® test. On the contrary, 23% (n = 30) of the patients with no indication were escalated to receive adjuvant chemotherapy after testing. Ki67 could not distinguish between the Prosigna® risk groups or intrinsic subtypes and did not significantly differ between patients in which decision for adjuvant therapy was changed based on the test results. In conclusion, we report the first real-world data from implementation of gene-expression-based risk assessment in a Swedish context, which may facilitate the optimization of future versions of the national guidelines.

Women with short survival after diagnosis of metastatic breast cancer: a population-based registry study.

PURPOSE: Despite therapeutic advances, overall survival of metastatic breast cancer (MBC) at the population level has seen little improvement over the past decades. Aggressive tumor biology or delay in access to cancer care might be contributing factors. With this retrospective population-based study we aimed to quantify and characterize patients with very short survival time following MBC diagnosis. METHODS: Women diagnosed with MBC between Jan 1st, 2005 and Dec 31st, 2016 were identified using the population-based Stockholm-Gotland breast cancer registry. Data regarding demographic and clinicopathological characteristics, survival, and treatment were extracted retrospectively from the registry and from patient charts. Patients who died within 90 days following diagnosis of MBC were identified and their characteristics were compared with all other patients diagnosed with MBC during the same period. RESULTS: Between 2005 and 2016, 3124 patients were diagnosed with MBC, of whom 498 (16.2%) died within 90 days of diagnosis. Nearly half (N = 233) did not receive any antitumoral treatment. Patients with short survival were older (p < 0.001), had higher primary tumor grade (p < 0.001), higher clinical stage at primary diagnosis (p = 0.002), and more often estrogen receptor (ER)-negative breast cancer (p < 0.001). Visceral metastases were more frequent (p < 0.001) and patients with short survival received adjuvant chemotherapy (p < 0.001) to a lesser extent compared to patients with a better prognosis. In multivariable analysis older age, time period of diagnosis, metastasis site, adjuvant chemotherapy, and primary tumor grade were independent predictors for short survival, whereas ER status was not. CONCLUSION: Nearly one out of six patients with MBC survive less than 3 months after diagnosis. Our findings demonstrate a different spectrum of MBC at population level and can potentially inform on individualized follow-up strategies and treatment algorithms.

Dissecting Tumor-Immune Microenvironment in Breast Cancer at a Spatial and Multiplex Resolution.

The tumor immune microenvironment (TIME) is an important player in breast cancer pathophysiology. Surrogates for antitumor immune response have been explored as predictive biomarkers to immunotherapy, though with several limitations. Immunohistochemistry for programmed death ligand 1 suffers from analytical problems, immune signatures are devoid of spatial information and histopathological evaluation of tumor infiltrating lymphocytes exhibits interobserver variability. Towards improved understanding of the complex interactions in TIME, several emerging multiplex in situ methods are being developed and gaining much attention for protein detection. They enable the simultaneous evaluation of multiple targets in situ, detection of cell densities/subpopulations as well as estimations of functional states of immune infiltrate. Furthermore, they can characterize spatial organization of TIME-by cell-to-cell interaction analyses and the evaluation of distribution within different regions of interest and tissue compartments-while digital imaging and image analysis software allow for reproducibility of the various assays. In this review, we aim to provide an overview of the different multiplex in situ methods used in cancer research with special focus on breast cancer TIME at the neoadjuvant, adjuvant and metastatic setting. Spatial heterogeneity of TIME and importance of longitudinal evaluation of TIME changes under the pressure of therapy and metastatic progression are also addressed.

Integrated multi-omics profiling of high-grade estrogen receptor-positive, HER2-negative breast cancer.

Estrogen receptor-positive and human epidermal growth factor receptor 2-negative (ER+ HER2- ) breast cancer accounts for ~ 60-70% of all cases of invasive breast carcinoma. High-grade ER+ HER2- tumors respond poorly to endocrine therapy. In this study, we systematically analyzed clinical and multi-omics data to find potential strategies for personalized therapy of patients with high-grade ER+ HER2- disease. Six different cohorts were analyzed, for which multi-omics data were available. Grade III ER+ HER2- cases harbored higher proportions of large tumor size (> 5 cm), lymph node metastasis, chemotherapy use, and luminal B subtypes defined by PAM50, as compared with grade I/II tumors. DNA methylation (HM450) data and methylation-specific PCR indicated that the cg18629132 locus in the MKI67 promoter was hypermethylated in grade I/II cases and normal tissue, but hypomethylated in grade III cases or triple-negative breast cancer, resulting in higher expression of MKI67. Mutations in ESR1 and TP53 were detected in post-endocrine treatment metastatic samples at a higher rate than in treatment-naive tumors in grade III cases. We identified 42 and 20 focal copy number events in nonmetastatic and metastatic high-grade ER+ HER2- cases, respectively, with either MYC or MDM2 amplification representing an independent prognostic event in grade III cases. Transcriptional profiling within grade III tumors highlighted ER signaling downregulation and upregulation of immune-related pathways in non-luminal-like tumors defined by PAM50. Recursive partitioning analysis was employed to construct a decision tree of an endocrine-resistant subgroup (GATA3-negative and AGR-negative) of two genes that was validated by immunohistochemistry in a Chinese cohort. All together, these data suggest that grade III ER+ HER2- tumors have distinct clinical and molecular characteristics compared with low-grade tumors, particularly in cases with non-luminal-like biology. Due to the dismal prognosis in this group, clinical trials are warranted to test the efficacy of potential novel therapies.