The long and winding road to biomarkers for immunotherapy: a retrospective analysis of samples from patients with triple-negative breast cancer treated with pembrolizumab.

BACKGROUND: Immune checkpoint blockade (ICB) in combination with chemotherapy improves outcome of patients with triple-negative breast cancer (TNBC) in metastatic and early settings. The identification of predictive biomarkers able to guide treatment decisions is challenging and currently limited to programmed death-ligand 1 (PD-L1) expression and high tumor mutational burden (TMB) in the advanced setting, with several limitations. MATERIALS AND METHODS: We carried out a retrospective analysis of clinical-pathological and molecular characteristics of tumor samples from 11 patients with advanced TNBC treated with single-agent pembrolizumab participating in two early-phase clinical trials: KEYNOTE-012 and KEYNOTE-086. Clinical, imaging, pathological [i.e. tumor-infiltrating lymphocytes (TILs), PD-L1 status], RNA sequencing, and whole-exome sequencing data were analyzed. We compared our results with publicly available transcriptomic data from TNBC cohorts from TCGA and METABRIC. RESULTS: Response to pembrolizumab was heterogeneous: two patients experienced exceptional long-lasting responses, six rapid progressions, and three relatively slower disease progression. Neither PD-L1 nor stromal TILs were significantly associated with response to treatment. Increased TMB values were observed in tumor samples from exceptional responders compared to the rest of the cohort (P = 3.4 × 10-4). Tumors from exceptional responders were enriched in adaptive and innate immune cell signatures. Expression of regulatory T-cell markers (FOXP3, CCR4, CCR8, TIGIT) was mainly observed in tumors from responders except for glycoprotein-A repetitions predominant (GARP), which was overexpressed in tumors from rapid progressors. GARP RNA expression in primary breast tumors from the public dataset was significantly associated with a worse prognosis. CONCLUSIONS: The wide spectrum of clinical responses to ICB supports that TNBC is a heterogeneous disease. Tumors with high TMB respond better to ICB. However, the optimal cut-off of 10 mutations (mut)/megabase (Mb) may not reflect the complexity of all tumor subtypes, despite its approval as a tumor-agnostic biomarker. Further studies are required to better elucidate the relevance of the tumor microenvironment and its components as potential predictive biomarkers in the context of ICB.

Genomic alterations in breast cancer: level of evidence for actionability according to ESMO Scale for Clinical Actionability of molecular Targets (ESCAT).

Better knowledge of the tumor genomic landscapes has helped to develop more effective targeted drugs. However, there is no tool to interpret targetability of genomic alterations assessed by next-generation sequencing in the context of clinical practice. Our aim is to rank the level of evidence of individual recurrent genomic alterations observed in breast cancer based on the ESMO Scale for Clinical Actionability of molecular Targets (ESCAT) in order to help the clinicians to prioritize treatment. Analyses of databases suggested that there are around 40 recurrent driver alterations in breast cancer. ERBB2 amplification, germline BRCA1/2 mutations, PIK3CA mutations were classified tier of evidence IA based on large randomized trials showing antitumor activity of targeted therapies in patients presenting the alterations. NTRK fusions and microsatellite instability (MSI) were ranked IC. ESR1 mutations and PTEN loss were ranked tier IIA, and ERBB2 mutations and AKT1 mutations tier IIB. Somatic BRCA 1/2 mutations, MDM2 amplifications and ERBB 3 mutations were ranked tier III. Seventeen genes were ranked tier IV based on preclinical evidence. Finally, FGFR1 and CCND1 were ranked tier X alterations because previous studies have shown lack of actionability.

Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning.

The extent of tumor-infiltrating lymphocytes (TILs), along with immunomodulatory ligands, tumor-mutational burden and other biomarkers, has been demonstrated to be a marker of response to immune-checkpoint therapy in several cancers. Pathologists have therefore started to devise standardized visual approaches to quantify TILs for therapy prediction. However, despite successful standardization efforts visual TIL estimation is slow, with limited precision and lacks the ability to evaluate more complex properties such as TIL distribution patterns. Therefore, computational image analysis approaches are needed to provide standardized and efficient TIL quantification. Here, we discuss different automated TIL scoring approaches ranging from classical image segmentation, where cell boundaries are identified and the resulting objects classified according to shape properties, to machine learning-based approaches that directly classify cells without segmentation but rely on large amounts of training data. In contrast to conventional machine learning (ML) approaches that are often criticized for their "black-box" characteristics, we also discuss explainable machine learning. Such approaches render ML results interpretable and explain the computational decision-making process through high-resolution heatmaps that highlight TILs and cancer cells and therefore allow for quantification and plausibility checks in biomedical research and diagnostics.

Trastuzumab versus observation for HER2 nonamplified early breast cancer with circulating tumor cells (EORTC 90091-10093, BIG 1-12, Treat CTC): a randomized phase II trial.

Background: Trastuzumab improves the outcome of women with HER2 positive breast cancer. We aimed to assess whether trastuzumab decreases the detection rate of circulating tumor cells (CTCs) in women with high risk, HER2 nonamplified, early breast cancer. Patients and methods: The EORTC 90091-10093 BIG 1-12 Treat CTC is a phase II trial, conducted in 70 hospitals and 6 CTC laboratories across 5 European countries. Patients with centrally confirmed HER2 nonamplified breast cancer and ≥1 centrally confirmed CTC per 15 ml of blood by CellSearch® following surgery and (neo)adjuvant chemotherapy were randomized (1 : 1) to 6 cycles of trastuzumab intravenously versus 18 weeks of observation. Randomization was stratified for center, locally confirmed estrogen receptor status and adjuvant versus neoadjuvant chemotherapy. The primary end point was rate of detection of ≥1 CTC per 15 ml of blood at week 18. Secondary end points were invasive disease-free survival (iDFS) and cardiac safety. Results: Between 30 April 2013 and 17 October 2016, 1317 patients were screened; 95 (7.2%) had detectable CTC(s), and 63 (4.8%) were randomized to trastuzumab (n = 31) or observation (n = 32). Fifty-eight patients were assessable for the primary end point, 29 in each arm. In 9 of the 58 patients, CTC(s) were still detected at week 18 : 5 in the trastuzumab and 4 in the observation arm (one-sided Fisher's exact test, P = 0.765). An Independent Data Monitoring Committee recommended stopping further accrual for futility for the primary end point. Median follow-up at database lock was 13 months (IQR 4-16.5). The 1-year iDFS was 93.8% (95% CI 77.3-98.4) in the observation versus 84.8% (95% CI 63.4-94.2) in the trastuzumab arm. No grade 2-4 cardiac events were observed in the trastuzumab arm. Conclusion: Trastuzumab does not decrease the detection rate of CTCs in HER2 nonamplified, nonmetastatic breast cancer.

Tumor metabolism assessed by FDG-PET/CT and tumor proliferation assessed by genomic grade index to predict response to neoadjuvant chemotherapy in triple negative breast cancer.

PURPOSE: Survival is increased when pathological complete response (pCR) is reached after neoadjuvant chemotherapy (NAC), especially in triple-negative breast cancer (TNBC) patients. Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (FDG) and the genomic grade index (GGI), each separately, showed good potential to predict pCR. Our study was designed to evaluate the predictive value for the therapeutic response of a combination of parameters based on FDG-PET, histoclinical features and molecular markers of proliferation. METHODS: Molecular parameters were measured on pre-treatment biopsy. Tumor metabolic activity was measured using two PET/CT scans, one before and one after 2 cycles of NAC. The pCR was determined on specimen after NAC. Event-free survival (EFS) was estimated using the Kaplan Meier method. RESULTS: Of 55 TNBC patients, 19 (35%) reached pCR after NAC. Tumor grade and Ki67 were not associated with pCR whereas GGI (P = 0.04) and its component KPNA2 (P = 0.04) showed a predictive value. The change of FDG uptake between PET1 and PET2 (ΔSUVmax) was highly associated with pCR (P = 0.0001) but the absolute value of baseline SUVmax was not (P = 0.11). However, the AUC of pCR prediction increased from 0.63 to 0.76 when baseline SUVmax was combined with the GGI (P = 0.016). The only two parameters associated with EFS were ΔSUVmax (P = 0.048) and pathological response (P = 0.014). CONCLUSIONS: The early tumor metabolic change during NAC is a powerful parameter to predict pCR and outcome in TNBC patients. The GGI, determined on pretreatment biopsy, is also predictive of pCR and the combination GGI and baseline SUVmax improves the prediction.

Immuno-oncology-101: overview of major concepts and translational perspectives.

Cancer immunotherapy is demonstrating impressive clinical benefit in different malignancies and clinical oncologists are increasingly turning their attention to immune-oncology. It is now well recognized that innate and adaptive immune cells infiltrating tumors are associated with clinical outcomes and responses to treatments, and can be harnessed to patients' benefit. Considerable advances have also been made in understanding how cancers escape from immune attack. Targeting of immunological escape processes regulated by the expression of immune checkpoint receptors and ligands and the down-modulation of tumor antigen presentation is the basis of immuno-oncology treatments. Despite recent achievements, there remain a number of unresolved issues in order to successfully implement cancer immunotherapy in many cancers. Importantly, clinical biomarkers are still needed for better optimization of emerging combination immunotherapies and better treatment tailoring. In this review, we summarize the function of innate and adaptive immune cells in anti-tumor immunity and the general mechanisms exploited by tumor cells to escape and inhibit immune responses as well as therapeutic strategies developed to overcome these mechanisms and discuss emerging biomarkers in immuno-oncology.

Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis.

Background: Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is known regarding the potential driving molecular events within each subtype, their difference in survival and response to therapy. Further insight into the underlying genomic alterations is therefore needed. Patients and methods: This study was carried out using copy-number aberrations, somatic mutations and gene expression data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas. TNBC samples (n = 550) were classified according to Lehmann's molecular subtypes using the TNBCtype online subtyping tool (http://cbc.mc.vanderbilt.edu/tnbc/). Results: Each subtype showed significant clinic-pathological characteristic differences. Using a multivariate model, IM subtype showed to be associated with a better prognosis (HR = 0.68; CI = 0.46-0.99; P = 0.043) whereas LAR subtype was associated with a worst prognosis (HR = 1.47; CI = 1.0-2.14; P = 0.046). BL1 subtype was found to be most genomically instable subtype with high TP53 mutation (92%) and copy-number deletion in genes involved in DNA repair mechanism (BRCA2, MDM2, PTEN, RB1 and TP53). LAR tumours were associated with higher mutational burden with significantly enriched mutations in PI3KCA (55%), AKT1 (13%) and CDH1 (13%) genes. M and MSL subtypes were associated with higher signature score for angiogenesis. Finally, IM showed high expression levels of immune signatures and check-point inhibitor genes such as PD1, PDL1 and CTLA4. Conclusion: Our findings highlight for the first time the substantial genomic heterogeneity that characterize TNBC molecular subtypes, allowing for a better understanding of the disease biology as well as the identification of several candidate targets paving novel approaches for the development of anticancer therapeutics for TNBC.

A gene signature to predict high tumor-infiltrating lymphocytes after neoadjuvant chemotherapy and outcome in patients with triple-negative breast cancer.

Background: In patients with triple-negative breast cancer (TNBC), the extent of tumor-infiltrating lymphocytes (TILs) in the residual disease after neoadjuvant chemotherapy (NACT) is associated with better prognosis. Our objective was to develop a gene signature from pretreatment samples to predict the extent of TILs after NACT and then to test its prognostic value on survival. Patients and methods: Using 99 pretreatment samples, we generated a four-gene signature associated with high post-NACT TILs. Prognostic value of the signature on distant relapse-free survival (DRFS) was first assessed on the training set (n = 99) and then on an independent validation set (n = 115). Results: A four-gene signature combining the expression levels of HLF, CXCL13, SULT1E1, and GBP1 was developed in baseline samples to predict the extent of lymphocytic infiltration after NACT. In a multivariate analysis performed on the training set, this signature was associated with DRFS [hazard ratio (HR): 0.28, for a one-unit increase in the value of the four-gene signature, 95% confidence interval (CI): 0.13-0.63)]. In a multivariate analysis performed on an independent validation set, the four-gene signature was significantly associated with DRFS (HR: 0.17, 95% CI: 0.06-0.43). The four-gene signature added significant prognostic information when compared with the clinicopathologic pretreatment model (likelihood ratio test in the training set P = 0.004 and in the validation set P = 0.002). Conclusions: A four-gene signature predicts high levels of TILs after anthracycline-containing NACT and outcome in patients with TNBC and adds prognostic information to a clinicopathological model at diagnosis.

Clinical significance of CD73 in triple-negative breast cancer: multiplex analysis of a phase III clinical trial.

Background: CD73 is an ecto-enzyme that promotes tumor immune escape through the production of immunosuppressive extracellular adenosine in the tumor microenvironment. Several CD73 inhibitors and adenosine receptor antagonists are being evaluated in phase I clinical trials. Patients and methods: Full-face sections from formalin-fixed paraffin-embedded primary breast tumors from 122 samples of triple-negative breast cancer (TNBC) from the BIG 02-98 adjuvant phase III clinical trial were included in our analysis. Using multiplex immunofluorescence and image analysis, we assessed CD73 protein expression on tumor cells, tumor-infiltrating leukocytes and stromal cells. We investigated the associations between CD73 protein expression with disease-free survival (DFS), overall survival (OS) and the extent of tumor immune infiltration. Results: Our results demonstrated that high levels of CD73 expression on epithelial tumor cells were significantly associated with reduced DFS, OS and negatively correlated with tumor immune infiltration (Spearman's R= -0.50, P < 0.0001). Patients with high levels of CD73 and low levels of tumor-infiltrating leukocytes had the worse clinical outcome. Conclusions: Taken together, our study provides further support that CD73 expression is associated with a poor prognosis and reduced anti-tumor immunity in human TNBC and that targeting CD73 could be a promising strategy to reprogram the tumor microenvironment in this BC subtype.

Tumor-infiltrating lymphocytes in patients with HER2-positive breast cancer treated with neoadjuvant chemotherapy plus trastuzumab, lapatinib or their combination: A meta-analysis of randomized controlled trials.

BACKGROUND: A relationship between baseline tumor-infiltrating lymphocytes (TIL) and outcomes has been described in HER2-positive breast cancer. Nevertheless, the magnitude of this association and whether this effect differs based on the type of anti-HER2 agent remain controversial. This meta-analysis investigated the association between baseline TIL and pathologic complete response (pCR) rates in HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab and lapatinib either alone or in combination. METHODS: A literature search covering PubMed, Embase and the Cochrane library up to October 31, 2016 identified randomized, controlled trials investigating neoadjuvant chemotherapy plus trastuzumab and lapatinib either alone or in combination where published data for pCR based on pre-treatment TIL scores were available. Two subgroups were considered: high baseline TIL vs. non-high TIL, according to each study definition. Summary risk estimates (odds ratio) and 95% confidence intervals (CI) were calculated for pCR using pre-treatment TIL levels for each trial. Pooled analyses were conducted using random and fixed effects models. Interaction P-values were computed using a Monte Carlo permutation test. RESULTS: A total of 5 studies (N=1256 patients) were included. Overall, high TIL subgroup was associated with a significantly increased pCR rate (OR 2.46; 95% CI 1.36-4.43; P=0.003). No interaction was observed between TIL subgroup (high vs. non-high TIL) and response to anti-HER2 agent(s) (trastuzumab vs. lapatinib vs. their combination; P=0.747) and chemotherapy (anthracycline and taxanes vs. taxanes only; P=0.201). A stronger association between high TIL subgroup and pCR rates was observed when examining only the 4 studies using anthracycline- and taxane- based neoadjuvant chemotherapy and the 60% cut-off for high TIL (N=869, NeoALTTO excluded) with an OR of 2.88 (95% CI 2.03-4.08; P<0.001). CONCLUSIONS: In HER2-positive breast cancer, high baseline TIL are associated with increased pCR probability irrespective of neoadjuvant anti-HER2 agent(s) and chemotherapy regimens used.

Pathway level alterations rather than mutations in single genes predict response to HER2-targeted therapies in the neo-ALTTO trial.

Background: We performed whole-exome sequencing of pretreatment biopsies and examined whether genome-wide metrics of overall mutational load, clonal heterogeneity or alterations at variant, gene, and pathway levels are associated with treatment response and survival. Patients and Methods: Two hundred and three biopsies from the NeoALTTO trial were analyzed. Mutations were called with MuTect, and Strelka, using pooled normal DNA. Associations between DNA alterations and outcome were evaluated by logistic and Cox-proportional hazards regression. Results: There were no recurrent single gene mutations significantly associated with pathologic complete response (pCR), except PIK3CA [odds ratio (OR) = 0.42, P = 0.0185]. Mutations in 33 of 714 pathways were significantly associated with response, but different genes were affected in different individuals. PIK3CA was present in 23 of these pathways defining a 'trastuzumab resistance-network' of 459 genes. Cases with mutations in this network had low pCR rates to trastuzumab (2/50, 4%) compared with cases with no mutations (9/16, 56%), OR = 0.035; P < 0.001. Mutations in the 'Regulation of RhoA activity' pathway were associated with higher pCR rate to lapatinib (OR = 14.8, adjusted P = 0.001), lapatinib + trastuzumab (OR = 3.0, adjusted P = 0.09), and all arms combined (OR = 3.77, adjusted P = 0.02). Patients (n = 124) with mutations in the trastuzumab resistance network but intact RhoA pathway had 2% (1/41) pCR rate with trastuzumab alone (OR = 0.026, P = 0.001) but adding lapatinib increased pCR rate to 45% (17/38, OR = 1.68, P = 0.3). Patients (n = 46) who had no mutations in either gene set had 6% pCR rate (1/15) with lapatinib, but had the highest pCR rate, 52% (8/15) with trastuzumab alone. Conclusions: Mutations in the RhoA pathway are associated with pCR to lapatinib and mutations in a PIK3CA-related network are associated with resistance to trastuzumab. The combined mutation status of these two pathways could define patients with very low response rate to trastuzumab alone that can be augmented by adding lapatinib or substituting trastuzumab with lapatinib.

Somatic mutation, copy number and transcriptomic profiles of primary and matched metastatic estrogen receptor-positive breast cancers.

BACKGROUND: Estrogen receptor-positive (ER+) breast cancers (BCs) constitute the most frequent BC subtype. The molecular landscape of ER+ relapsed disease is not well characterized. In this study, we aimed to describe the genomic evolution between primary (P) and matched metastatic (M) ER+ BCs after failure of adjuvant therapy. MATERIALS AND METHODS: A total of 182 ER+ metastatic BC patients with long-term follow-up were identified from a single institution. P tumor tissue was available for all patients, with 88 having matched M material. According to the availability of tumor material, samples were characterized using a 120 mutational hotspot qPCR, a 29 gene copy number aberrations (CNA) and a 400 gene expression panels. ESR1 mutations were assayed by droplet digital PCR. Molecular alterations were correlated with overall survival (OS) using the Cox proportional hazards regression models. RESULTS: The median follow-up was 6.4 years (range 0.5-26.6 years). Genomic analysis of P tumors revealed somatic mutations in PIK3CA, KRAS, AKT1, FGFR3, HRAS and BRAF at frequencies of 41%, 6%, 5%, 2%, 1% and 2%, respectively, and CN amplification of CCND1, ZNF703, FGFR1, RSF1 and PAK1 at 23%, 19%, 17%, 12% and 11%, respectively. Mutations and CN amplifications were largely concordant between P and matched M (>84%). ESR1 mutations were found in 10.8% of the M but none of the P. Thirteen genes, among which ESR1, FOXA1, and HIF1A, showed significant differential expression between P and M. In P, the differential expression of 18 genes, among which IDO1, was significantly associated with OS (FDR < 0.1). CONCLUSIONS: Despite the large concordance between P and matched M for the evaluated molecular alterations, potential actionable targets such as ESR1 mutations were found only in M. This supports the importance of characterizing the M disease. Other targets we identified, such as HIF1A and IDO1, warrant further investigation in this patient population.

PIK3CA mutations are associated with reduced pathological complete response rates in primary HER2-positive breast cancer: pooled analysis of 967 patients from five prospective trials investigating lapatinib and trastuzumab.

BACKGROUND: The predictive value of PIK3CA mutations in HER2 positive (HER2+) breast cancer treated with neoadjuvant anti-HER2 and chemotherapy has been reported, but the power for subgroup analyses was lacking. PATIENTS AND METHODS: We combined individual patient data from five clinical trials evaluating PIK3CA mutations and associations with pathological complete response (pCR), disease-free survival (DFS) and overall survival (OS). Patients received either trastuzumab (T), lapatinib (L) or the combination T/L in addition to a taxane-based chemotherapy. PIK3CA was genotyped in tumour biopsies taken before therapy. RESULTS: A total of 967 patients were included in this analysis; the median follow-up is 47 months. Overall, the pCR rate was significantly lower in the PIK3CA mutant compared with the wild-type group (16.2% versus 29.6%; P < 0.001). Within the hormone-receptor positive (HR+) subgroup, the PIK3CA mutant group had a pCR rate of only 7.6% compared with 24.2% in the wild-type group (P < 0.001). In contrast, in the HER2+/HR- group, there was no difference in pCR (27.2% versus 36.4%; P = 0.125) according to PIK3CA mutation status (interaction test P = 0.036). According to treatment arm, the pCR rate for mutant versus wild-type was 20.3% versus 27.1% for T (P = 0.343), 11.3% versus 16.9% for L (P = 0.369) and 16.7% versus 39.1% for T/L (P < 0.001). In the HR+ T/L group, the pCR rate was 5.5% versus 33.9% (interaction between HR and PIK3CA genotype P = 0.008). DFS and OS were not significantly different by mutation status, though the incidence rate of events was low. However, HR+/PIK3CA mutant patients seemed to have significantly worse DFS {hazard ratio (HR) 1.56 [95% confidence interval (CI) 1.00-2.45], P = 0.050; Pinteraction = 0.021}. T/L tended to improve DFS compared with T in the wild-type cohort, especially in the HR- group [HR 0.72, 95% CI (0.41-1.25), P = 0.242]. CONCLUSION: Overall PIK3CA mutant/HER2+ tumours had significantly lower pCR rates compared with wild-type tumours, however mainly confined to the HR+/PIK3CA mutant population. No definite conclusions can be drawn regarding survival.

Consensus on precision medicine for metastatic cancers: a report from the MAP conference.

Recent advances in biotechnologies have led to the development of multiplex genomic and proteomic analyses for clinical use. Nevertheless, guidelines are currently lacking to determine which molecular assays should be implemented in metastatic cancers. The first MAP conference was dedicated to exploring the use of genomics to better select therapies in the treatment of metastatic cancers. Sixteen consensus items were covered. There was a consensus that new technologies like next-generation sequencing of tumors and ddPCR on circulating free DNA have convincing analytical validity. Further work needs to be undertaken to establish the clinical utility of liquid biopsies and the added clinical value of expanding from individual gene tests into large gene panels. Experts agreed that standardized bioinformatics methods for biological interpretation of genomic data are needed and that precision medicine trials should be stratified based on the level of evidence available for the genomic alterations identified.

The current use and attitudes towards tumor genome sequencing in breast cancer.

There is increasing availability of technologies that can interrogate the genomic landscape of an individual tumor; however, their impact on daily practice remains uncertain. We conducted a 28-item survey to investigate the current attitudes towards the integration of tumor genome sequencing in breast cancer management. A link to the survey was communicated via newsletters of several oncological societies, and dedicated mailing by academic research groups. Multivariable logistic regression modeling was carried out to determine the relationship between predictors and outcomes. 215 physicians participated to the survey. The majority were medical oncologists (88%), practicing in Europe (70%) and working in academic institutions (66%). Tumor genome sequencing was requested by 82 participants (38%), of whom 21% reported low confidence in their genomic knowledge, and 56% considered tumor genome sequencing to be poorly accessible. In multivariable analysis, having time allocated to research (OR 3.37, 95% CI 1.84-6.15, p < 0.0001), working in Asia (OR 5.76, 95% CI 1.57 - 21.15, p = 0.01) and having institutional guidelines for molecular sequencing (OR 2.09, 95% 0.99-4.42, p = 0.05) were associated with a higher probability of use. In conclusion, our survey indicates that tumor genome sequencing is sometimes used, albeit not widely, in guiding management of breast cancer patients.