Martin Malmberg

Molecular subtype and tumor characteristics of breast cancer metastases as assessed by gene expression significantly influence patient post-relapse survival

An enhanced understanding of the biology of breast cancer metastases is needed to individualize patient management. Here, we show that tumor characteristics of breast cancer metastases significantly influence post-relapse survival, emphasizing that molecular investigation at relapse offers clinically relevant information, with the potential to improve patient management and survival.BACKGROUND We and others have recently shown that tumor characteristics are altered throughout tumor progression. These findings emphasize the need for re-examination of tumor characteristics at relapse and have led to recommendations from ESMO and the Swedish Breast Cancer group. Here, we aim to determine whether tumor characteristics and molecular subtypes in breast cancer metastases confer clinically relevant prognostic information for patients. PATIENTS AND METHODS The translational aspect of the Swedish multicenter randomized trial called TEX included 111 patients with at least one biopsy from a morphologically confirmed locoregional or distant breast cancer metastasis diagnosed from December 2002 until June 2007. All patients had detailed clinical information, complete follow-up, and metastasis gene expression information (Affymetrix array GPL10379). We assessed the previously published gene expression modules describing biological processes [proliferation, apoptosis, human epidermal receptor 2 (HER2) and estrogen (ER) signaling, tumor invasion, immune response, and angiogenesis] and pathways (Ras, MAPK, PTEN, AKT-MTOR, PI3KCA, IGF1, Src, Myc, E2F3, and β-catenin) and the intrinsic subtypes (PAM50). Furthermore, by contrasting genes expressed in the metastases in relation to survival, we derived a poor metastasis survival signature. RESULTS A significant reduction in post-relapse breast cancer-specific survival was associated with low-ER receptor signaling and apoptosis gene module scores, and high AKT-MTOR, Ras, and β-catenin module scores. Similarly, intrinsic subtyping of the metastases provided statistically significant post-relapse survival information with the worst survival outcome in the basal-like [hazard ratio (HR) 3.7; 95% confidence interval (CI) 1.3-10.9] and HER2-enriched (HR 4.4; 95% CI 1.5-12.8) subtypes compared with the luminal A subtype. Overall, 25% of the metastases were basal-like, 32% HER2-enriched, 10% luminal A, 28% luminal B, and 5% normal-like. CONCLUSIONS We show that tumor characteristics and molecular subtypes of breast cancer metastases significantly influence post-relapse patient survival, emphasizing that molecular investigations at relapse provide prognostic and clinically relevant information. CLINICALTRIALS.GOV: This is the translational part of the Swedish multicenter and randomized trial TEX, clinicaltrials.gov identifier nct01433614 (http://www.clinicaltrials.gov/ct2/show/nct01433614).

Targeted sequencing of BRCA1 and BRCA2 across a large unselected breast cancer cohort suggests that one-third of mutations are somatic

We carried out targeted sequencing of BRCA1/2 in an unselected cohort of patients diagnosed with primary breast cancer within a population without strong founder mutations. Eleven percent of cases harbored a germline or somatic BRCA1/2 mutation, and the ratio of germline versus somatic mutation was 2 : 1. This has implications for treatment, genetic counseling, and interpretation of tumor-only testing.

An investigation of routes to cancer diagnosis in 10 international jurisdictions, as part of the International Cancer Benchmarking Partnership: survey development and implementation

Objectives This paper describes the methods used in the International Cancer Benchmarking Partnership Module 4 Survey (ICBPM4) which examines time intervals and routes to cancer diagnosis in 10 jurisdictions. We present the study design with defining and measuring time intervals, identifying patients with cancer, questionnaire development, data management and analyses. Design and setting Recruitment of participants to the ICBPM4 survey is based on cancer registries in each jurisdiction. Questionnaires draw on previous instruments and have been through a process of cognitive testing and piloting in three jurisdictions followed by standardised translation and adaptation. Data analysis focuses on comparing differences in time intervals and routes to diagnosis in the jurisdictions. Participants Our target is 200 patients with symptomatic breast, lung, colorectal and ovarian cancer in each jurisdiction. Patients are approached directly or via their primary care physician (PCP). Patients’ PCPs and cancer treatment specialists (CTSs) are surveyed, and ‘data rules’ are applied to combine and reconcile conflicting information. Where CTS information is unavailable, audit information is sought from treatment records and databases. Main outcomes Reliability testing of the patient questionnaire showed that agreement was complete (κ=1) in four items and substantial (κ=0.8, 95% CI 0.333 to 1) in one item. The identification of eligible patients is sufficient to meet the targets for breast, lung and colorectal cancer. Initial patient and PCP survey response rates from the UK and Sweden are comparable with similar published surveys. Data collection was completed in early 2016 for all cancer types. Conclusion An international questionnaire-based survey of patients with cancer, PCPs and CTSs has been developed and launched in 10 jurisdictions. ICBPM4 will help to further understand international differences in cancer survival by comparing time intervals and routes to cancer diagnosis.

Minimizing inequality in access to precision medicine in breast cancer by real-time population-based molecular analysis in the SCAN-B initiative

Selection of systemic therapy for primary breast cancer is currently based on clinical biomarkers along with stage. Novel genomic tests are continuously being introduced as more precise tools for guidance of therapy, although they are often developed for specific patient subgroups. The Sweden Cancerome Analysis Network – Breast (SCAN‐B) initiative aims to include all patients with breast cancer for tumour genomic analysis, and to deliver molecular subtype and mutational data back to the treating physician.

Immune gene expression and response to chemotherapy in advanced breast cancer

Background:Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting.Methods:In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method.Results:Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03–2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43–10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders.Conclusions:Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.

Validation of the predictive value of tissue inhibitor of metalloproteinases-1 for the response to first-line chemotherapy in metastatic breast cancer.

CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts Abstract #6057 *Wurtz SO and Klintman M contributed equally, Malstrom P and Brunner N shares the senior authorship. Background. Predictive markers are scarcely represented in breast cancer. TIMP-1 has in a previous study (n = 173) performed in our laboratory been shown to carry predictive information for the response to chemotherapy in metastatic breast cancer as high tumor tissue levels of TIMP-1 were significantly associated with a low objective response rate to treatment with the most frequently used chemotherapeutic drugs (CMF or anthracyclines). The purpose of the present study was to validate these previous results with a new independent patient population. Methods. The TIMP-1 level was measured using a validated ELISA in 168 primary tumor extracts from patients with metastatic breast cancer and levels were associated with the objective response to CMF and anthracyclines. Patients were included in the study provided that they had received chemotherapy for their metastatic disease and that frozen tumor tissue as well as data on their objective response to chemotherapy was available. Results. The median TIMP-1 level in responders was 17.3 (2.9 – 75.8) ng TIMP-1/mg protein and in non-responders it was 19.6 (0-190.3) ng TIMP-1/mg protein. When analysed as a continuous log-transformed variable, increasing tumor levels of TIMP-1 were associated with a decreasing probability of objective response to CMF or anthracyclines (OR = 1.59, 95% CI: 0.97 – 2.62, p = 0.07). This is very similar to the original study and thus supporting previous data. Next, we used a more clinically relevant approach for analysing the data from the validation study. For this analysis, objective response was scored as complete or partial response versus stable disease lasting at least six months (clinical benefit) versus progressive disease (non-response). This analysis showed that increasing levels of TIMP-1 were associated with a poor clinical benefit rate from chemotherapy (OR = 1.56, 95% CI: 0.98 - 2.51, p=0.06). The original study has not previously been analysed using this endpoint. When performing this analysis, similar results were found (OR = 1.62, 95% CI: 1.06 - 2.48, p = 0.02). Combining the new population and the original population in a pooled analysis (n = 341) using a random effects model showed that high levels of TIMP-1 were highly significantly associated with a poor clinical benefit rate from chemotherapy compared with patients with low levels (OR = 1.59, 95% CI: 1.16 - 2.18, p=0.003). Conclusion. The present validation study supports previous findings that primary tumor tissue levels of TIMP-1 carries predictive information in metastatic breast cancer treated with chemotherapy. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 6057.

Clinical Value of RNA Sequencing–Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network—Breast Initiative

Purpose In early breast cancer (BC), five conventional biomarkers—estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)—are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification. Methods In total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network—Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses. Results Pathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non–hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34). Conclusion Classification error rates for RNA-seq–based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.

Abstract P3-02-02: Concordance between immunohistochemical and gene-expression based subtyping of early breast cancer using core needle biopsies and surgical specimens - experices from SCAN-B

Introduction: Preoperative chemotherapy in early breast cancer increases the rate of breast preservation and provides prognostic information. Treatment decisions in these cases rely on biomarker assessments and subtyping from tissue acquired through core needle biopsies. Tumor heterogeneity and representativity are pit-falls when limited tissue is available. Biomarker expression may change considerably as a result of preoperative chemotherapy, and in a subset of cases a complete pathological response at time of surgery may even preclude any further assessment. Therefore, the reliability and reproducibility of biomarkers in base-line core biopsies are of utmost importance for patients treated with preoperative chemotherapy.Material and Methods: In an ongoing population-based study of early breast cancer, the SCAN-B (NCT02306096), patients were identified for whom an ultra-sound guided core needle biopsy was analyzed for biomarkers during primary clinical work-up and the patient was offered primary surgery as initial treatment. Clinical biomarker profiles including immunohistochemical (IHC) determinations of ER, PgR, HER2 and Ki67 were translated to subtypes according to modified St Gallen criteria (2013) and compared with paired samples from surgical specimens. In addition, tumor specimens for biomolecule extraction and RNA sequencing were collected fresh in RNAlater.Results: IHC data was available from 51 paired samples. The subtype distribution in core needle biopsies was DCIS in 1 case (2 %), LCIS in 1 case (2 %) Luminal A-like in 16 cases (31 %), Luminal B-like (HER2 negative) in 26 cases (51 %), Luminal B-HER2-like (HER2 positive) in 4 cases (8 %), HER2-positive (non-luminal) in 1 case (2 %) and triple negative (ductal) breast cancer in 2 cases (4 %). The subtype distribution in surgical specimens was DCIS in 0 case (0 %), LCIS in 1 case (2 %) Luminal A-like in 18 cases (35 %), Luminal B-like (HER2negative) in 23 cases (45 %), Luminal B--like (HER2 positive) in 6 cases (12 %), HER2-positive (non-luminal) in 1 case (2 %) and triple negative (ductal) breast cancer in 2 cases (4 %). Notably, 5/16 cases classified as Luminal A-like in the core needle biopsy were reclassified as Luminal B-like (HER2-negative) in the surgical specimen, whereas 9/26 cases classified as Luminal B-like (HER2-negative) in the core needle biopsy were reclassified as either Luminal A-like (7 cases) or Luminal B-like (HER2 positive) (2 cases) in the surgical specimen. In all instances, except one, transition between Luminal A-like and Luminal B-like was due to recorded Ki67 expression. One case that was classified as a DCIS in the core needle was reclassified as Luminal B-like (HER2 negative) at time of surgery.Discussion: In this limited material, discordance between evaluations regarding Luminal A-like and Luminal B-like was considerable. Especially the misclassification of primary HER2-positive breast cancer needs further evaluation. These findings may be caused by tumor heterogeneity, and highlight the risk of both over- and under-treatment upon biomarker assessment from core needle biopsies. Data from gene expression based subtype classifications will be presented during the meeting.

Abstract P2-02-09: Breast cancer subtype distribution and circulating tumor DNA in response to neoadjuvant chemotherapy: Experiences from a preoperative cohort within SCAN-B

Introduction: Preoperative chemotherapy in early breast cancer increases the rate of breast preservation and provides prognostic information. In the case of residual disease, a change in subtypes may be observed. Sensitive and reproducible biomarkers predicting treatment response early during the treatment course are needed in order to better exploit the potential benefit of an individualized preoperative treatment.Material and Methods: In an ongoing prospective study within the population-based SCAN-B project (NCT02306096), patients undergoing preoperative chemotherapy for early or locally recurrent breast cancer have been treated with iv Epirubicin and Cyclophosphamide q3w x 3 in sequence with either Docetaxel q3w x 3 or Paclitaxel q1w x 9 with a preoperative intent. HER2-positive cases also received HER2-directed treatment. At baseline, patients were staged using sentinel node biopsy for clinically node-negative patients and CT scan for cytologically confirmed node-positive cases. A clinical core needle biopsy as well as tissue from the surgical specimen was collected for determination of conventional biomarkers including ER, PgR, HER2 and Ki67. Tumor biopsies for biomolecule-extraction and RNA-sequencing were taken using ultrasound guidance and collected fresh in RNAlater at baseline, after 2 treatment cycles, as well as at surgery. Blood plasma samples were collected at baseline, after one-, three-, and six- 3w treatment cycles, and post-surgery. Using RNA-sequencing data, somatic mutations were identified in the tumor biopsies and personalized analyses for circulating tumor DNA (ctDNA) were performed. A pathological complete remission (pCR) was defined as the complete disappearance of invasive breast cancer in the breast and axilla at time of definitive surgery. Subtyping was performed using modified St Gallen criteria (2013).Results: Thus far, 45 patients aged 24-74 years have been included, of which 34 (76 %) were clinical stage 2 and 11 (24%) were stage 3. The subtype distribution at baseline was five Luminal A-like (11 %), 21 Luminal B-like (HER2 negative) (47 %), 8 HER2-positive (18 %) and 11 Triple-negative (ductal) (24 %). The rates of pCR in 38 operated cases to date were 0/3 Luminal A-like, 3/19 Luminal B-like (HER2 negative), 2/8 HER2-positive, and 4/7 Triple-negative (overall 24 % pCR rate). One patient did not undergo surgery due to clinically progressive disease. In 25 cases with evaluable residual disease at surgery, there was a shift in the subtype in 13 (52 %), the majority of which represented a transition from Luminal B to Luminal A. No Triple-negative cases underwent a change in subtype during treatment. Results of the ctDNA analyses will be presented at the meeting.Discussion: We have established an infrastructure allowing for an extensive evaluation of preoperative chemotherapy in early breast cancer. The goal is to develop methods to refine response-guided treatment in early breast cancer using molecular responses in the tumor as well as in the blood circulation. The patients continue to be prospectively monitored with iterative ctDNA analyses during follow-up.

Abstract P4-09-03: On the development and clinical value of RNA-sequencing-based classifiers for prediction of the five conventional breast cancer biomarkers: A report from the population-based multicenter SCAN-B study

Background:In early breast cancer, five histopathological biomarkers are part of current clinical routines and used for determining prognosis and treatment: estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (ERBB2/HER2), Ki67, and Nottingham histological grade (NHG). We aimed to develop classifiers for these biomarkers based on tumor mRNA-sequencing (RNA-seq), compare classification performance to conventional histopathology, and test whether RNA-seq-based predictors could add value for patient risk-stratification.Patients and Methods:In total, 3678 breast tumors were studied. For 405 breast tumors in the training cohort, a comprehensive histopathological biomarker evaluation was performed by three pathology readings to estimate inter-pathologist variability on the original diagnostic slides as well as on repeat immunostains for this study, and the consensus biomarker status for all five conventional biomarkers was determined. Whole transcriptome gene expression profiling was performed by RNA-sequencing on the Illumina platform. Using RNA-seq-derived tumor gene expression data as input, single-gene classifiers (SGC) and multi-gene classifiers (MGC) were trained on the consensus pathology biomarker labels. The trained classifiers were tested on an independent prospective population-based series of 3273 primary breast cancer cases from the multicenter SCAN-B study with median 41 months follow-up (ClinicalTrials.gov identifier NCT02306096), and classifications were evaluated by agreement statistics and by Kaplan-Meier and Cox regression survival analyses.Results:For the histopathological evaluation, pathologist evaluation concordance was high for ER, PgR, and HER2 (average kappa values of .920, .891, and .899, respectively), but moderate for Ki67 and NHG (.734 and .581). Classification concordance between RNA-seq classifiers and histopathology for the independent 3273-cohort was similar to that within histopathology assessments, with SGCs slightly outperforming MGCs. Importantly, patients with discordant results, classified as hormone responsive (HoR+) by histopathology but non-hormone responsive by MGC, presented with significantly inferior overall survival compared to patients with concordant results. These results extended to patients with no adjuvant systemic therapy (hazard ratio, HR, 4.54; 95% confidence interval, CI, 1.42-14.5), endocrine therapy alone (HR 3.46; 95% CI, 2.01-5.95), or receiving chemotherapy (HR 2.57; 95% CI 1.13-5.86). For HoR+ cases receiving endocrine therapy alone, the MGC HoR classifier remained significant after multivariable adjustment (HR 3.14; 95% CI, 1.75-5.65).Conclusions:RNA-seq-based classifiers for the five key early breast cancer biomarkers were generally equivalent to conventional histopathology with regards to classification error rate. However, when benchmarked using overall survival, our RNA-seq classifiers provided added clinical value in particular for cases that are determined by histopathology to be hormone-responsive but by RNA-seq appear hormone-insensitive and have a significantly poorer outcome when treated with endocrine therapy alone