Stefan Michiels

Somatic Mutation Profiling and Associations With Prognosis and Trastuzumab Benefit in Early Breast Cancer

Background Certain somatic alterations in breast cancer can define prognosis and response to therapy. This study investigated the frequencies, prognostic effects, and predictive effects of known cancer somatic mutations using a randomized, adjuvant, phase III clinical trial dataset. Methods The FinHER trial was a phase III, randomized adjuvant breast cancer trial involving 1010 women. Patients with human epidermal growth factor receptor 2 (HER2)–positive breast cancer were further randomized to 9 weeks of trastuzumab or no trastuzumab. Seven hundred five of 1010 tumors had sufficient DNA for genotyping of 70 somatic hotspot mutations in 20 genes using mass spectrometry. Distant disease-free survival (DDFS), overall survival (OS), and interactions with trastuzumab were explored with Kaplan-Meier and Cox regression analyses. All statistical tests were two-sided. Results Median follow-up was 62 months. Of 705 tumors, 687 were successfully genotyped. PIK3CA mutations (exons 1, 2, 4, 9, 13, 18, and 20) were present in 25.3% (174 of 687) and TP53 mutations in 10.2% (70 of 687). Few other mutations were found: three ERBB2 and single cases of KRAS, ALK, STK11/LKB1, and AKT2. PIK3CA mutations were associated with estrogen receptor positivity (P < .001) and the luminal-A phenotype (P = .04) but were not statistically significantly associated with prognosis (DDFS: hazard ratio [HR] = 0.88, 95% confidence [CI] = 0.58 to 1.34, P = .56; OS: HR = 0.603, 95% CI = .32 to 1.13, P = .11), although a statistically significant nonproportional prognostic effect was observed for DDFS (P = .002). PIK3CA mutations were not statistically significantly associated with trastuzumab benefit (P interaction: DDFS P = .14; OS P = .24). Conclusions In this dataset, targeted genotyping revealed only two alterations at a frequency greater than 10%, with other mutations observed infrequently. PIK3CA mutations were associated with a better outcome, however this effect disappeared after 3 years. There were no statistically significant associations with trastuzumab benefit.

High-Throughput Genomics and Clinical Outcome in Hard-to-Treat Advanced Cancers: Results of the MOSCATO 01 Trial

High-throughput genomic analyses may improve outcomes in patients with advanced cancers. MOSCATO 01 is a prospective clinical trial evaluating the clinical benefit of this approach. Nucleic acids were extracted from fresh-frozen tumor biopsies and analyzed by array comparative genomic hybridization, next-generation sequencing, and RNA sequencing. The primary objective was to evaluate clinical benefit as measured by the percentage of patients presenting progression-free survival (PFS) on matched therapy (PFS2) 1.3-fold longer than the PFS on prior therapy (PFS1). A total of 1,035 adult patients were included, and a biopsy was performed in 948. An actionable molecular alteration was identified in 411 of 843 patients with a molecular portrait. A total of 199 patients were treated with a targeted therapy matched to a genomic alteration. The PFS2/PFS1 ratio was >1.3 in 33% of the patients (63/193). Objective responses were observed in 22 of 194 patients (11%; 95% CI, 7%-17%), and median overall survival was 11.9 months (95% CI, 9.5-14.3 months).Significance: This study suggests that high-throughput genomics could improve outcomes in a subset of patients with hard-to-treat cancers. Although these results are encouraging, only 7% of the successfully screened patients benefited from this approach. Randomized trials are needed to validate this hypothesis and to quantify the magnitude of benefit. Expanding drug access could increase the percentage of patients who benefit. Cancer Discov; 7(6); 586-95. ©2017 AACR.See related commentary by Schram and Hyman, p. 552This article is highlighted in the In This Issue feature, p. 539.

Tumour-infiltrating lymphocytes in advanced HER2-positive breast cancer treated with pertuzumab or placebo in addition to trastuzumab and docetaxel: a retrospective analysis of the CLEOPATRA study

BACKGROUNDnHigh quantities of tumour-infiltrating lymphocytes (TILs) in primary HER2-positive breast cancer are associated with improved prognosis and response to therapy. We aimed to investigate the prognostic role of host antitumour immunity as represented by baseline quantities of TILs in patients with advanced HER2-positive breast cancer treated with either pertuzumab or placebo in addition to trastuzumab and docetaxel.nnnMETHODSnCLEOPATRA was a randomised phase 3 study comparing the addition of either pertuzumab or placebo to first-line therapy with trastuzumab and docetaxel for patients with locally recurrent, unresectable, or metastatic HER2-positive breast cancer. We assessed the quantity of stromal TILs in prospectively collected tumour samples and investigated their association with progression-free survival, overall survival, clinicopathological characteristics, and pertuzumab treatment. We estimated hazard ratios (HR) and 95% CIs with multivariate Cox regression models fitting stromal TILs as a continuous variable (per 10% increment). The CLEOPATRA trial is registered with ClinicalTrials.gov, number NCT00567190.nnnFINDINGSnTumour samples from 678 (84%) of 808 participants were evaluable for TILs, including 519 (77%) archival samples, 155 (23%) freshly obtained samples (collected 45 days or fewer before randomisation), and four samples of unknown archival status. Median follow-up was 50 months (IQR 41-54) for progression-free survival and 51 months (IQR 46-57) for overall survival. 519 progression-free survival events occurred and 358 patients died. The median TIL value was 10% (IQR 5-30). Freshly obtained tumour samples had significantly lower TIL values than did archival samples (10·00% [95% CI 5·00-20·00] vs 15·00% [5·00-35·00]; p=0·00036). We detected no significant association between TIL values and progression-free survival (adjusted HR 0·95, 95% CI 0·90-1·00, p=0·063). However, for overall survival, each 10% increase in stromal TILs was significantly associated with longer overall survival (adjusted HR 0·89, 95% CI 0·83-0·96, p=0·0014). The treatment effect of pertuzumab did not differ significantly by stromal TIL value for either progression-free survival (pinteraction=0·23) or overall survival (pinteraction=0·21).nnnINTERPRETATIONnIn patients with advanced HER2-positive breast cancer treated with docetaxel, trastuzumab, and pertuzumab or placebo, higher TIL values are significantly associated with improved overall survival, suggesting that the effect of antitumour immunity extends to the advanced setting. Future clinical studies in this cancer subtype should consider TILs as a stratification factor and investigate whether therapies that can augment immunity could potentially further improve survival.nnnFUNDINGnF Hoffmann-La Roche-Genentech and the Breast Cancer Research Foundation.

Predictors of responses to immune checkpoint blockade in advanced melanoma

Immune checkpoint blockers (ICB) have become pivotal therapies in the clinical armamentarium against metastatic melanoma (MMel). Given the frequency of immune related adverse events and increasing use of ICB, predictors of response to CTLA-4 and/or PD-1 blockade represent unmet clinical needs. Using a systems biology-based approach to an assessment of 779 paired blood and tumor markers in 37 stage III MMel patients, we analyzed association between blood immune parameters and the functional immune reactivity of tumor-infiltrating cells after ex vivo exposure to ICB. Based on this assay, we retrospectively observed, in eight cohorts enrolling 190 MMel patients treated with ipilimumab, that PD-L1 expression on peripheral T cells was prognostic on overall and progression-free survival. Moreover, detectable CD137 on circulating CD8+ T cells was associated with the disease-free status of resected stage III MMel patients after adjuvant ipilimumabu2009+u2009nivolumab (but not nivolumab alone). These biomarkers should be validated in prospective trials in MMel.The clinical management of metastatic melanoma requires predictors of the response to checkpoint blockade. Here, the authors use immunological assays to identify potential prognostic/predictive biomarkers in circulating blood cells and in tumor-infiltrating lymphocytes from patients with resected stage III melanoma.

Update on tumor-infiltrating lymphocytes (TILs) in breast cancer, including recommendations to assess TILs in residual disease after neoadjuvant therapy and in carcinoma in situ: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Morphological evaluation of tumor-infiltrating lymphocytes (TILs) in breast cancer is gaining momentum as evidence strengthens the clinical relevance of this immunological biomarker. TILs in the post-neoadjuvant residual disease setting are acquiring increasing importance as a stratifying marker in clinical trials, considering the raising interest on immunotherapeutic strategies after neoadjuvant chemotherapy. TILs in ductal carcinoma in situ, with or without invasive carcinoma, represent an emerging area of clinical breast cancer research. The aim of this report is to update pathologists, clinicians and researchers on TIL assessment in both the post-neoadjuvant residual disease and the ductal carcinoma in situ settings. The International Immuno-Oncology Working Group proposes a method for assessing TILs in these settings, based on the previously published International Guidelines on TIL Assessment in Breast Cancer. In this regard, these recommendations represent a consensus guidance for pathologists, aimed to achieve the highest possible consistency among future studies.

Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.

Correct selection of prognostic biomarkers among multiple candidates is becoming increasingly challenging as the dimensionality of biological data becomes higher. Therefore, minimizing the false discovery rate (FDR) is of primary importance, while a low false negative rate (FNR) is a complementary measure. The lasso is a popular selection method in Cox regression, but its results depend heavily on the penalty parameter λ. Usually, λ is chosen using maximum cross-validated log-likelihood (max-cvl). However, this method has often a very high FDR. We review methods for a more conservative choice of λ. We propose an empirical extension of the cvl by adding a penalization term, which trades off between the goodness-of-fit and the parsimony of the model, leading to the selection of fewer biomarkers and, as we show, to the reduction of the FDR without large increase in FNR. We conducted a simulation study considering null and moderately sparse alternative scenarios and compared our approach with the standard lasso and 10 other competitors: Akaike information criterion (AIC), corrected AIC, Bayesian information criterion (BIC), extended BIC, Hannan and Quinn information criterion (HQIC), risk information criterion (RIC), one-standard-error rule, adaptive lasso, stability selection, and percentile lasso. Our extension achieved the best compromise across all the scenarios between a reduction of the FDR and a limited raise of the FNR, followed by the AIC, the RIC, and the adaptive lasso, which performed well in some settings. We illustrate the methods using gene expression data of 523 breast cancer patients. In conclusion, we propose to apply our extension to the lasso whenever a stringent FDR with a limited FNR is targeted. Copyright

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

BACKGROUNDnEstrogen 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.nnnMATERIALS AND METHODSnA 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.nnnRESULTSnThe 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).nnnCONCLUSIONSnDespite 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.

Multiple testing of treatment-effect modifying biomarkers in a randomized clinical trial with a survival endpoint

The recent revolution in genomics and the advent of targeted therapies have increased interest in biomarker-defined subgroups of patients who respond to therapy or exhibit specific toxicities. Such biomarker-defined subgroups are also being investigated for non-targeted therapies (e.g. chemotherapy and statins). However, even when the targeting pathway has been identified, a broadly available test to identify the appropriate subgroup will rarely exist prior to the launch of the pivotal phase III trial. Our aim in this paper is to provide guidance for the analysis of a phase III clinical trial with a survival endpoint, in order to ascertain whether a therapy is more effective in the biomarker-positive patients as compared with biomarker-negative patients, when the trial is conducted on the entire population and when there are multiple candidate biomarkers. We studied treatment-by-biomarker interactions in a Weibull regression model. Different permutation procedures, using single-biomarker statistics and novel composite statistics, are proposed in order to control the family-wise error rate accounting for dependence structures among the biomarkers. A simulation study was performed to compare the operational characteristics of the permutation tests under different scenarios. The tests were applied to a phase III trial of adjuvant chemotherapy in early breast cancer, for which 10 biomarkers were measured in tumor samples from 798 patients. These permutation tests can be applied to retrospective biomarker studies and to prospective phase III trials of new drugs for which a few clues are known about the targeting pathway at the start of the trial.

Statistical controversies in clinical research: prognostic gene signatures are not (yet) useful in clinical practice

With the genomic revolution and the era of targeted therapy, prognostic and predictive gene signatures are becoming increasingly important in clinical research. They are expected to assist prognosis assessment and therapeutic decision making. Notwithstanding, an evidence-based approach is needed to bring gene signatures from the laboratory to clinical practice. In early breast cancer, multiple prognostic gene signatures are commercially available without having formally reached the highest levels of evidence-based criteria. We discuss specific concepts for developing and validating a prognostic signature and illustrate them with contemporary examples in breast cancer. When a prognostic signature has not been developed for predicting the magnitude of relative treatment benefit through an interaction effect, it may be wishful thinking to test its predictive value. We propose that new gene signatures be built specifically for predicting treatment effects for future patients and outline an approach for this using a cross-validation scheme in a standard phase III trial. Replication in an independent trial remains essential.

Improved treatment of breast cancer with anti-HER2 therapy requires interleukin-21 signaling in CD8+ T cells

The HER2/ErbB2 monoclonal antibody (mAb) trastuzumab is combined with chemotherapy as a standard-of-care for newly diagnosed HER2(+) breast cancer patients, but some patients treated with this combination therapy experience early relapse. Our analysis of data from a clinical trial evaluating the efficacy of chemotherapy plus/minus trastuzumab suggested that the magnitude of trastuzumab benefit on distant disease-free survival was higher for increasing expression of the IL21 receptor (IL21R). Therefore, we investigated a possible role for IL21 signaling in promoting HER2 mAb therapeutic efficacy. We found that IL21R-deficient mice and wild-type mice treated with a neutralizing anti-IL21 mAb were less susceptible to trastuzumab-like anti-ErbB2 therapy. Furthermore, IL21R expression on CD8(+) T cells, but not on natural killer cells, was required for optimal anti-ErbB2 mAb efficacy, and IL21 expression was enhanced in tumor-infiltrating CD4(+) T lymphocytes after anti-ErbB2 therapy. Finally, we found that administering recombinant IL21 in combination with anti-ErbB2 therapy was therapeutic against primary tumors and experimental metastases in mice. Collectively, our findings suggest that elevating IL21 signaling may enhance trastuzumab efficacy, thus constituting a novel candidate strategy to overcome trastuzumab resistance and improve patient survival. Cancer