Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727).

PURPOSE: The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers. EXPERIMENTAL DESIGN: Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers. RESULTS: Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR. CONCLUSIONS: High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.

Molecular profiling of aromatase inhibitor sensitive and resistant ER+HER2- postmenopausal breast cancers.

Aromatase inhibitors (AIs) reduce recurrences and mortality in postmenopausal patients with oestrogen receptor positive (ER+) breast cancer (BC), but >20% of patients will eventually relapse. Given the limited understanding of intrinsic resistance in these tumours, here we conduct a large-scale molecular analysis to identify features that impact on the response of ER + HER2- BC to AI. We compare the 15% of poorest responders (PRs, n = 177) as measured by proportional Ki67 changes after 2 weeks of neoadjuvant AI to good responders (GRs, n = 190) selected from the top 50% responders in the POETIC trial and matched for baseline Ki67 categories. In this work, low ESR1 levels are associated with poor response, high proliferation, high expression of growth factor pathways and non-luminal subtypes. PRs having high ESR1 expression have similar proportions of luminal subtypes to GRs but lower plasma estradiol levels, lower expression of estrogen response genes, higher levels of tumor infiltrating lymphocytes and immune markers, and more TP53 mutations.

Efficacy and Safety of TRC105 Plus Pazopanib vs Pazopanib Alone for Treatment of Patients With Advanced Angiosarcoma: A Randomized Clinical Trial.

Importance: Angiosarcoma is a rare sarcoma subtype with a poor outcome. Carotuximab plus pazopanib produced a median progression-free survival (PFS) of 7.8 months in pazopanib-naive patients with chemotherapy-refractory angiosarcoma in a phase 1/2 trial. Objective: To determine whether carotuximab plus pazopanib improves PFS compared with pazopanib alone in patients with advanced angiosarcoma. Design, Setting, and Participants: The TAPPAS Trial: An Adaptive Enrichment Phase 3 Trial of TRC105 and Pazopanib vs Pazopanib Alone in Patients With Advanced Angiosarcoma was a multinational, multicenter, open-label, parallel-group, phase 3 randomized clinical trial of 123 patients 18 years or older with advanced angiosarcoma that was conducted between February 16, 2017, and April 12, 2019, at 31 sites in the US and the European Union. Patients were randomized 1:1 to receive pazopanib alone or carotuximab plus pazopanib. The trial incorporated an adaptive enrichment design. Inclusion criteria were no more than 2 prior lines of systemic therapy and an Eastern Cooperative Oncology Group performance status of 0 or 1. The efficacy analysis used the intent-to-treat population; the safety analysis included all patients who received a dose of either study drug. Exposures: Oral pazopanib, 800 mg/d, or intravenous carotuximab, 10 mg/kg, administered weekly, plus oral pazopanib, 800 mg/d, with dose modification allowed per patient tolerance or until disease progression. Main Outcomes and Measures: The primary end point was PFS, assessed by blinded independent radiographic and cutaneous photographic review per Response Evaluation Criteria in Solid Tumors (RECIST) guidelines, version 1.1. Secondary end points included the objective response rate and overall survival. An interim analysis to determine the final sample size was conducted after enrollment of 123 patients. PFS in the group receiving pazopanib alone was compared with PFS in the group receiving carotuximab plus pazopanib using the log rank test. Results: Of 114 patients with evaluable data (53 in the pazopanib arm and 61 in the carotuximab plus pazopanib arm), 69 (61%) were female and the median age was 68 years (range, 24-82 years); 57 (50%) had cutaneous disease and 32 (28%) had had no prior treatment. The primary end point (PFS) was not reached (hazard ratio [HR], 0.98; 95% CI, 0.52-1.84; P = .95), with a median of 4.3 months (95% CI, 2.9 months to not reached) for pazopanib and 4.2 months (95% CI, 2.8-8.3 months) for the combination arm. The most common all-grade adverse events in the single-agent pazopanib arm vs the combination arm were fatigue (29 patients [55%] vs 37 [61%]), headache (12 patients [23%] vs 39 [64%]), diarrhea (27 patients [51%] vs 35 [57%]), nausea (26 patients [49%] vs 29 [48%]), vomiting (12 patients [23%] vs 23 [38%]), anemia (5 patients [9%] vs 27 [44%]), epistaxis (2 patients [4%] vs 34 [56%]), and hypertension (29 patients [55%] vs 22 [36%]). Conclusions and Relevance: In this phase 3 randomized clinical trial, carotuximab plus pazopanib did not improve PFS compared with pazopanib alone in patients with advanced angiosarcoma. Trial Registration: ClinicalTrials.gov Identifier: NCT02979899.

Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler.

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.

Impact of the menstrual cycle on commercial prognostic gene signatures in oestrogen receptor-positive primary breast cancer.

PURPOSE: Changes occur in the expression of oestrogen-regulated and proliferation-associated genes in oestrogen receptor (ER)-positive breast tumours during the menstrual cycle. We investigated if Oncotype® DX recurrence score (RS), Prosigna® (ROR) and EndoPredict® (EP/EPclin) prognostic tests, which include some of these genes, vary according to the time in the menstrual cycle when they are measured. METHODS: Pairs of test scores were derived from 30 ER-positive/human epidermal growth factor receptor-2-negative tumours sampled at two different points of the menstrual cycle. Menstrual cycle windows were prospectively defined as either W1 (days 1-6 and 27-35; low oestrogen and low progesterone) or W2 (days 7-26; high oestrogen and high or low progesterone). RESULTS: The invasion module score of RS was lower (- 10.9%; p = 0.098), whereas the ER (+ 16.6%; p = 0.046) and proliferation (+ 7.3%; p = 0.13) module scores were higher in W2. PGR expression was significantly increased in W2 (+ 81.4%; p = 0.0029). Despite this, mean scores were not significantly different between W1 and W2 for any of the tests and the two measurements showed high correlation (r = 0.72-0.93). However, variability between the two measurements led to tumours being assigned to different risk categories in the following proportion of cases: RS 22.7%, ROR 27.3%, EP 13.6% and EPclin 13.6%. CONCLUSION: There are significant changes during the menstrual cycle in the expression of some of the genes and gene module scores comprising the RS, ROR and EP/EPclin scores. These did not affect any of the prognostic scores in a systematic fashion, but there was substantial variability in paired measurements.

Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®.

Multi-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2- breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (rc(RS) = 0.96, 95% CI 0.93-0.97 with level of agreement (LoA) of -7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96-0.98 with LoA of -0.64 to 1.26 and rc(ROR) = 0.97 (95% CI 0.94-0.98) with LoA of -8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer.

Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Identifying Biomarkers to Pair with Targeting Treatments within Triple Negative Breast Cancer for Improved Patient Stratification.

The concept of precision medicine has been around for many years and recent advances in high-throughput sequencing techniques are enabling this to become reality. Within the field of breast cancer, a number of signatures have been developed to molecularly sub-classify tumours. Notable examples recently approved by National Institute for Health and Care Excellence in the UK to guide treatment decisions for oestrogen receptors (ER)+ human epidermal growth factor receptor 2 (HER2)- patients include Prosigna test, EndoPredict, and Oncotype DX. However, a population of still unmet need are those with triple negative breast cancer (TNBC). Accounting for 15-20% of patients, this population has comparatively poor prognosis and as yet no targeted treatment options. Studies have shown that some patients with TNBC respond favourably to DNA damaging drugs (carboplatin) or agents which inhibit DNA damage response (poly ADP ribose polymerase (PARP) inhibitors). Known to be a heterogeneous population, there is a need to identify further TNBC patients who may benefit from these treatments. A number of signatures have been identified based on association with treatment response or specific genetic features/pathways however many of these were not restricted to TNBC patients and as of yet are not common practice in the clinic.

Heterocellular gene signatures reveal luminal-A breast cancer heterogeneity and differential therapeutic responses.

Breast cancer is a highly heterogeneous disease. Although differences between intrinsic breast cancer subtypes have been well studied, heterogeneity within each subtype, especially luminal-A cancers, requires further interrogation to personalize disease management. Here, we applied well-characterized and cancer-associated heterocellular signatures representing stem, mesenchymal, stromal, immune, and epithelial cell types to breast cancer. This analysis stratified the luminal-A breast cancer samples into five subtypes with a majority of them enriched for a subtype (stem-like) that has increased stem and stromal cell gene signatures, representing potential luminal progenitor origin. The enrichment of immune checkpoint genes and other immune cell types in two (including stem-like) of the five heterocellular subtypes of luminal-A tumors suggest their potential response to immunotherapy. These immune-enriched subtypes of luminal-A tumors (containing only estrogen receptor positive samples) showed good or intermediate prognosis along with the two other differentiated subtypes as assessed using recurrence-free and distant metastasis-free patient survival outcomes. On the other hand, a partially differentiated subtype of luminal-A breast cancer with transit-amplifying colon-crypt characteristics showed poor prognosis. Furthermore, published luminal-A subtypes associated with specific somatic copy number alterations and mutations shared similar cellular and mutational characteristics to colorectal cancer subtypes where the heterocellular signatures were derived. These heterocellular subtypes reveal transcriptome and cell-type based heterogeneity of luminal-A and other breast cancer subtypes that may be useful for additional understanding of the cancer type and potential patient stratification and personalized medicine.

Dissecting the predictive value of MAPK/AKT/estrogen-receptor phosphorylation axis in primary breast cancer to treatment response for tamoxifen over exemestane: a Translational Report of the Intergroup Exemestane Study (IES)-PathIES.

PURPOSE: The prognostic and predictive values of the MAPK/AKT/ERα phosphorylation axis (pT202/T204MAPK, pT308AKT, pS473AKT, pS118ERα and pS167ERα) in primary tumours were assessed to determine whether these markers can differentiate between patient responses for switching adjuvant endocrine therapy after 2-3 years from tamoxifen to exemestane and continued tamoxifen monotherapy in the Intergroup Exemestane Study (IES). METHODS: Of the 4724 patients in IES, 1506 were managed in a subset of centres (N = 89) participating in PathIES. These centres recruited 1282 (85%, 1282/1506) women into PathIES of whom 1036 had phospho-marker data. All phospho-markers were analysed by immunohistochemistry staining. Multivariable Cox proportional hazards models of the phospho-markers for disease-free survival (DFS) and overall survival (OS) were adjusted for clinicopathological factors. Treatment effects on the biomarker expression were determined by interaction tests. Benjamini-Hochberg adjustment for multiple testing with a false discovery rate of 10% was applied (pBH). RESULTS: Phospho-T202/T204MAPK, pS118ERα and pS167ERα were all found to be correlated (pBH = 0.0002). These markers were not associated with either DFS or OS when controlling for the established clinicopathological factors. Interaction terms between the phospho-markers and treatment strategies for either DFS or OS were not statistically significant (pBH > 0.05 for all). CONCLUSIONS: This PathIES study confirmed previously described associations between the phosphorylation site markers of AKT, MAPK and ERα activity in postmenopausal breast cancer patients. No prognostic correlations between the phosphorylation markers and clinical outcome were found, nor were they predictive for clinical outcomes among patients who switched therapy over those treated with tamoxifen alone.

Genomic Instability and TP53 Genomic Alterations Associate With Poor Antiproliferative Response and Intrinsic Resistance to Aromatase Inhibitor Treatment.

PURPOSE: Although aromatase inhibitor (AI) treatment is effective in estrogen receptor-positive postmenopausal breast cancer, resistance is common and incompletely explained. Genomic instability, as measured by somatic copy number alterations (SCNAs), is important in breast cancer development and prognosis. SCNAs to specific genes may drive intrinsic resistance, or high genomic instability may drive tumor heterogeneity, which allows differential response across tumors and surviving cells to evolve resistance to treatment rapidly. We therefore evaluated the relationship between SCNAs and intrinsic resistance to treatment as measured by a poor antiproliferative response. PATIENTS AND METHODS: SCNAs were determined by single nucleotide polymorphism array in baseline and surgery core-cuts from 73 postmenopausal patients randomly assigned to receive 2 weeks of preoperative AI or no AI in the Perioperative Endocrine Therapy-Individualizing Care (POETIC) trial. Fifty-six samples from the AI group included 28 poor responders (PrRs, less than 60% reduction in protein encoded by the MKI67 gene [Ki-67]) and 28 good responders (GdRs, greater than 75% reduction in Ki-67). Exome sequencing was available for 72 pairs of samples. RESULTS: Genomic instability correlated with Ki-67 expression at both baseline (P < .001) and surgery (P < .001) and was higher in PrRs (P = .048). The SCNA with the largest difference between GdRs and PrRs was loss of heterozygosity observed at 17p (false discovery rate, 0.08), which includes TP53. Nine of 28 PrRs had loss of wild-type TP53 as a result of mutations and loss of heterozygosity compared with three of 28 GdRs. In PrRs, somatic alterations of TP53 were associated with higher genomic instability, higher baseline Ki-67, and greater resistance to AI treatment compared with wild-type TP53. CONCLUSION: We observed that primary tumors with high genomic instability have an intrinsic resistance to AI treatment and do not require additional evolution to develop resistance to estrogen deprivation therapy.

Impact of aromatase inhibitor treatment on global gene expression and its association with antiproliferative response in ER+ breast cancer in postmenopausal patients.

BACKGROUND: Endocrine therapy reduces breast cancer mortality by 40%, but resistance remains a major clinical problem. In this study, we sought to investigate the impact of aromatase inhibitor (AI) therapy on gene expression and identify gene modules representing key biological pathways that relate to early AI therapy resistance. METHODS: Global gene expression was measured on pairs of core-cut biopsies taken at baseline and at surgery from 254 patients with ER-positive primary breast cancer randomised to receive 2-week presurgical AI (n = 198) or no presurgical treatment (control n = 56) from the POETIC trial. Data from the AI group was adjusted to eliminate artefactual process-related changes identified in the control group. The response was assessed by changes in the proliferation marker, Ki67. RESULTS: High baseline ESR1 expression associated with better AI response in HER2+ tumours but not HER2- tumours. In HER2- tumours, baseline expression of 48 genes associated with poor antiproliferative response (p < 0.005) including PERP and YWHAQ, the two most significant, and the transcription co-regulators (SAP130, HDAC4, and NCOA7) which were among the top 16 most significant. Baseline gene signature scores measuring cell proliferation, growth factor signalling (ERBB2-GS, RET/GDNF-GS, and IGF-1-GS), and immune activity (STAT1-GS) were significantly higher in poor AI responders. Two weeks of AI caused downregulation of genes involved in cell proliferation and ER signalling, as expected. Signature scores of E2F activation and TP53 dysfunction after 2-week AI were associated with poor AI response in both HER2- and HER2+ patients. CONCLUSIONS: There is a high degree of heterogeneity in adaptive mechanisms after as little as 2-week AI therapy; however, all appear to converge on cell cycle regulation. Our data support the evaluation of whether an E2F signatures after short-term exposure to AI may identify those patients most likely to benefit from the early addition of CDK4/6 inhibitors. TRIAL REGISTRATION: ISRCTN, ISRCTN63882543, registered on 18 December 2007.

Randomized Phase II Study Evaluating Palbociclib in Addition to Letrozole as Neoadjuvant Therapy in Estrogen Receptor-Positive Early Breast Cancer: PALLET Trial.

PURPOSE: CDK4/6 inhibitors are used to treat estrogen receptor (ER)-positive metastatic breast cancer (BC) in combination with endocrine therapy. PALLET is a phase II randomized trial that evaluated the effects of combination palbociclib plus letrozole as neoadjuvant therapy. PATIENTS AND METHODS: Postmenopausal women with ER-positive primary BC and tumors greater than or equal to 2.0 cm were randomly assigned 3:2:2:2 to letrozole (2.5 mg/d) for 14 weeks (A); letrozole for 2 weeks, then palbociclib plus letrozole to 14 weeks (B); palbociclib for 2 weeks, then palbociclib plus letrozole to 14 weeks (C); or palbociclib plus letrozole for 14 weeks. Palbociclib 125 mg/d was administered orally on a 21-days-on, 7-days-off schedule. Core-cut biopsies were taken at baseline and 2 and 14 weeks. Coprimary end points for letrozole versus palbociclib plus letrozole groups (A v B + C + D) were change in Ki-67 (protein encoded by the  MKI67 gene; immunohistochemistry) between baseline and 14 weeks and clinical response (ordinal and ultrasound) after 14 weeks. Complete cell-cycle arrest was defined as Ki-67 less than or equal to 2.7%. Apoptosis was characterized by cleaved poly (ADP-ribose) polymerase. RESULTS: Three hundred seven patients were recruited. Clinical response was not significantly different between palbociclib plus letrozole and letrozole groups ( P = .20; complete response + partial response, 54.3% v 49.5%), and progressive disease was 3.2% versus 5.4%, respectively. Median log-fold change in Ki-67 was greater with palbociclib plus letrozole compared with letrozole (-4.1 v -2.2; P < .001) in the 190 evaluable patients (61.9%), corresponding to a geometric mean change of -97.4% versus -88.5%. More patients on palbociclib plus letrozole achieved complete cell-cycle arrest (90% v 59%; P < .001). Median log-fold change (suppression) of cleaved poly (ADP-ribose) polymerase was greater with palbociclib plus letrozole versus letrozole (-0.80 v -0.42; P < .001). More patients had grade 3 or greater toxicity on palbociclib plus letrozole (49.8% v 17.0%; P < .001) mainly because of asymptomatic neutropenia. CONCLUSION: Adding palbociclib to letrozole significantly enhanced the suppression of malignant cell proliferation (Ki-67) in primary ER-positive BC, but did not increase the clinical response rate over 14 weeks, which was possibly related to a concurrent reduction in apoptosis.

Novel 18-gene signature for predicting relapse in ER-positive, HER2-negative breast cancer.

BACKGROUND: Several prognostic signatures for early oestrogen receptor-positive (ER+) breast cancer have been established with a 10-year follow-up. We tested the hypothesis that signatures optimised for 0-5-year and 5-10-year follow-up separately are more prognostic than a single signature optimised for 10 years. METHODS: Genes previously identified as prognostic or associated with endocrine resistance were tested in publicly available microarray data set using Cox regression of 747 ER+/HER2- samples from post-menopausal patients treated with 5 years of endocrine therapy. RNA expression of the selected genes was assayed in primary ER+/HER2- tumours from 948 post-menopausal patients treated with 5 years of anastrozole or tamoxifen in the TransATAC cohort. Prognostic signatures for 0-10, 0-5 and 5-10 years were derived using a penalised Cox regression (elastic net). Signature comparison was performed with likelihood ratio statistics. Validation was done by a case-control (POLAR) study in 422 samples derived from a cohort of 1449. RESULTS: Ninety-three genes were selected by the modelling of microarray data; 63 of these were significantly prognostic in TransATAC, most similarly across each time period. Contrary to our hypothesis, the derived early and late signatures were not significantly more prognostic than the 18-gene 10-year signature. The 18-gene 10-year signature was internally validated in the TransATAC validation set, showing prognostic information similar to that of Oncotype DX Recurrence Score, PAM50 risk of recurrence score, Breast Cancer Index and IHC4 (score based on four IHC markers), as well as in the external POLAR case-control set. CONCLUSIONS: The derived 10-year signature predicts risk of metastasis in patients with ER+/HER2- breast cancer similar to commercial signatures. The hypothesis that early and late prognostic signatures are significantly more informative than a single signature was rejected.

Carboplatin in BRCA1/2-mutated and triple-negative breast cancer BRCAness subgroups: the TNT Trial.

Germline mutations in BRCA1/2 predispose individuals to breast cancer (termed germline-mutated BRCA1/2 breast cancer, gBRCA-BC) by impairing homologous recombination (HR) and causing genomic instability. HR also repairs DNA lesions caused by platinum agents and PARP inhibitors. Triple-negative breast cancers (TNBCs) harbor subpopulations with BRCA1/2 mutations, hypothesized to be especially platinum-sensitive. Cancers in putative 'BRCAness' subgroups-tumors with BRCA1 methylation; low levels of BRCA1 mRNA (BRCA1 mRNA-low); or mutational signatures for HR deficiency and those with basal phenotypes-may also be sensitive to platinum. We assessed the efficacy of carboplatin and another mechanistically distinct therapy, docetaxel, in a phase 3 trial in subjects with unselected advanced TNBC. A prespecified protocol enabled biomarker-treatment interaction analyses in gBRCA-BC and BRCAness subgroups. The primary endpoint was objective response rate (ORR). In the unselected population (376 subjects; 188 carboplatin, 188 docetaxel), carboplatin was not more active than docetaxel (ORR, 31.4% versus 34.0%, respectively; P = 0.66). In contrast, in subjects with gBRCA-BC, carboplatin had double the ORR of docetaxel (68% versus 33%, respectively; biomarker, treatment interaction P = 0.01). Such benefit was not observed for subjects with BRCA1 methylation, BRCA1 mRNA-low tumors or a high score in a Myriad HRD assay. Significant interaction between treatment and the basal-like subtype was driven by high docetaxel response in the nonbasal subgroup. We conclude that patients with advanced TNBC benefit from characterization of BRCA1/2 mutations, but not BRCA1 methylation or Myriad HRD analyses, to inform choices on platinum-based chemotherapy. Additionally, gene expression analysis of basal-like cancers may also influence treatment selection.

Intrinsic subtypes and benefit from postmastectomy radiotherapy in node-positive premenopausal breast cancer patients who received adjuvant chemotherapy - results from two independent randomized trials.

BACKGROUND: The study of the intrinsic molecular subtypes of breast cancer has revealed differences among them in terms of prognosis and response to chemotherapy and endocrine therapy. However, the ability of intrinsic subtypes to predict benefit from adjuvant radiotherapy has only been examined in few studies. METHODS: Gene expression-based intrinsic subtyping was performed in 228 breast tumors collected from two independent post-mastectomy clinical trials (British Columbia and the Danish Breast Cancer Cooperative Group 82b trials), where pre-menopausal patients with node-positive disease were randomized to adjuvant radiotherapy or not. All patients received adjuvant chemotherapy and a subgroup of patients underwent ovarian ablation. Tumors were classified into intrinsic subtypes: Luminal A, Luminal B, HER2-enriched, Basal-like and Normal-like using the research-based PAM50 classifier. RESULTS: In the British Columbia study, patients treated with radiation had an overall significant lower incidence of locoregional recurrence compared to the controls. For Luminal A tumors the risk of loco-regional recurrence was low and was further lowered by adjuvant radiation. These findings were validated in the DBCG 82b study. The individual data from the two cohorts were merged, the hazard ratio (HR) for loco-regional recurrence associated with giving radiation was 0.34 (0.19 to 0.61) overall and 0.12 (0.03 to 0.52) for Luminal A tumors. CONCLUSIONS: In both postmastectomy trials, patients with Luminal A tumors turned out to have a significant lower incidence of loco-regional recurrence when randomized to adjuvant radiotherapy, leaving no indication to omit postmastectomy adjuvant radiation in pre-menopausal high-risk patients with Luminal A tumors. It was not possible to evaluate the effect of radiotherapy among the other subtypes because of limited sample sizes.