Optimal targeting of PI3K-AKT and mTOR in advanced oestrogen receptor-positive breast cancer.

The growing availability of targeted therapies for patients with advanced oestrogen receptor-positive breast cancer has improved survival, but there remains much to learn about the optimal management of these patients. The PI3K-AKT and mTOR pathways are among the most commonly activated pathways in breast cancer, whose crucial role in the pathogenesis of this tumour type has spurred major efforts to target this pathway at specific kinase hubs. Approvals for oestrogen receptor-positive advanced breast cancer include the PI3K inhibitor alpelisib for PIK3CA-mutated tumours, the AKT inhibitor capivasertib for tumours with alterations in PIK3CA, AKT1, or PTEN, and the mTOR inhibitor everolimus, which is used irrespective of mutation status. The availability of different inhibitors leaves physicians with a potentially challenging decision over which of these therapies should be used for individual patients and when. In this Review, we present a comprehensive summary of our current understanding of the pathways and the three inhibitors and discuss strategies for the optimal sequencing of therapies in the clinic, particularly after progression on a CDK4/6 inhibitor.

RB1 Genetic Alterations in Estrogen Receptor-Positive Breast Carcinomas: Correlation With Neuroendocrine Differentiation.

Genetic alterations in the retinoblastoma susceptibility gene (RB1) are present in up to 40% of triple-negative breast cancers (BCs) and frequent in tumors with neuroendocrine differentiation, including small cell neuroendocrine carcinoma. Data on RB1 genetic alterations in estrogen receptor (ER)-positive BCs are scarce. In this study, we sought to define the morphologic, immunohistochemical, and genetic features of ER-positive BCs harboring somatic alterations in RB1, with emphasis on neuroendocrine differentiation. ER-positive BCs with pathogenic RB1 genetic alterations were identified in <1% of cases (N = 55) from a cohort of 6026 BCs previously subjected to targeted next-generation sequencing, including 23 primary BCs (pBCs) and 32 recurrent/metastatic BCs (mBCs). In cases where loss of heterozygosity of the wild-type RB1 allele could be assessed (93%, 51/55), most pBCs (82%, 18/22) and mBCs (90%, 26/29) exhibited biallelic RB1 inactivation, primarily through loss-of-function mutation and loss of heterozygosity (98%, 43/44). Upon histologic review, a subset of RB1-altered tumors exhibited neuroendocrine morphology (13%, 7/55), which correlated with expression of neuroendocrine markers (39%, 9/23) in both pBCs (27%, 3/11) and mBCs (50%, 6/12). Loss of Rb protein expression was observed in BCs with biallelic RB1 loss only, with similar frequency in pBCs (82%, 9/11) and mBCs (75%, 9/12). All cases with neuroendocrine marker expression (n = 9) and/or neuroendocrine morphology (n = 7) harbored biallelic genetic inactivation of RB1 and exhibited Rb loss of expression. TP53 (53%, 29/55) and PIK3CA (45%, 25/55) were the most frequently comutated genes across the cohort. Overall, these findings suggest that ER-positive BCs with biallelic RB1 genetic alterations frequently exhibit Rb protein loss, which correlates with neuroendocrine differentiation in select BCs. This study provides insights into the molecular and phenotypic heterogeneity of BCs with RB1 genetic inactivation, underscoring the need for further research into the potential clinical implications associated with these tumors.

Management of patients with advanced-stage HER2-positive breast cancer: current evidence and future perspectives.

Amplification and/or overexpression of ERBB2, the gene encoding HER2, can be found in 15-20% of invasive breast cancers and is associated with an aggressive phenotype and poor clinical outcomes. Relentless research efforts in molecular biology and drug development have led to the implementation of several HER2-targeted therapies, including monoclonal antibodies, tyrosine-kinase inhibitors and antibody-drug conjugates, constituting one of the best examples of bench-to-bedside translation in oncology. Each individual drug class has improved patient outcomes and, importantly, the combinatorial and sequential use of different HER2-targeted therapies has increased cure rates in the early stage disease setting and substantially prolonged survival for patients with advanced-stage disease. In this Review, we describe key steps in the development of the modern paradigm for the treatment of HER2-positive advanced-stage breast cancer, including selecting and sequencing new-generation HER2-targeted therapies, and summarize efficacy and safety outcomes from pivotal studies. We then outline the factors that are currently known to be related to resistance to HER2-targeted therapies, such as HER2 intratumoural heterogeneity, activation of alternative signalling pathways and immune escape mechanisms, as well as potential strategies that might be used in the future to overcome this resistance and further improve patient outcomes.

Pathologic complete response to KEYNOTE522 and HER2-directed therapy for synchronous TNBC and HER2+ breast cancer.

Simultaneous presentation of two separate primary breast cancers of differing histology at initial diagnosis is an uncommon phenomenon; it is even rarer to find these pathologically distinct populations within the same biopsy. Here we report the case of a patient diagnosed with clearly demarcated, pathologically heterogenous triple negative breast cancer (TNBC) and HER2+ breast cancer that was treated with a hybrid chemoimmunotherapy regimen combining elements of Keynote-522 and a standard HER2-directed neoadjuvant regimen, yielding apathologic complete response by the time of surgery with no notable adverse events. Molecular analysis of the histologically distinct tumor populations confirmed molecular evidence of differential HER2 expression but also suggested clonal relatedness of the two tumor populations based upon mutational profile, with phenotypic divergence potentially resulting from copy number alterations in NF1. Overall, this case highlights a rare histologic phenomenon that was successfully treated by combining both TNBC and HER2 directed neoadjuvant therapies.

Predictors of Response to CDK4/6i Retrial After Prior CDK4/6i Failure in ER+ Metastatic Breast Cancer.

After disease progression on endocrine therapy (ET) plus a CDK4/6 inhibitor, there is no standardized sequence for subsequent treatment lines for estrogen receptor positive (ER+) metastatic breast cancer (MBC). CDK4/6i retrial as a treatment strategy is commonplace in modern clinical practice; however, the available prospective data investigating this strategy have had inconclusive results. To frame this data in a real-world context, we performed a retrospective analysis assessing the efficacy of CDK4/6is in 195 patients who had previous exposure to CDK4/6i in a prior treatment line at our institution. Among patients who had stopped a CDK4/6i due to toxicity, CDK4/6i retrial either immediately after with a different CDK4/6i or in a further treatment line with the same initial CDK4/6i was both safe and effective, with a median time to treatment failure (TTF) of 10.1 months (95%CI, 4.8-16.9). For patients whose disease progressed on a prior CDK4/6i, we demonstrated comparable median TTFs for patients rechallenged with the same CDK4/6i (4.3 months, 95%CI 3.2-5.5) and with a different CDK4/6i (4.7 months, 95%CI 3.7-6.0) when compared to the recent PACE, PALMIRA, and MAINTAIN trials. Exploratory genomic analysis suggested that the presence of mutations known to confer CDK4/6i resistance, such as TP53 mutations, CDK4 amplifications, and RB1 or FAT1 loss of function mutations may be molecular biomarkers predictive of CDK4/6i retrial failure.

APOBEC3 mutagenesis drives therapy resistance in breast cancer.

Acquired genetic alterations commonly drive resistance to endocrine and targeted therapies in metastatic breast cancer 1-7 , however the underlying processes engendering these diverse alterations are largely uncharacterized. To identify the mutational processes operant in breast cancer and their impact on clinical outcomes, we utilized a well-annotated cohort of 3,880 patient samples with paired tumor-normal sequencing data. The mutational signatures associated with apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3 (APOBEC3) enzymes were highly prevalent and enriched in post-treatment compared to treatment-naïve hormone receptor-positive (HR+) cancers. APOBEC3 mutational signatures were independently associated with shorter progression-free survival on antiestrogen plus CDK4/6 inhibitor combination therapy in patients with HR+ metastatic breast cancer. Whole genome sequencing (WGS) of breast cancer models and selected paired primary-metastatic samples demonstrated that active APOBEC3 mutagenesis promoted resistance to both endocrine and targeted therapies through characteristic alterations such as RB1 loss-of-function mutations. Evidence of APOBEC3 activity in pre-treatment samples illustrated a pervasive role for this mutational process in breast cancer evolution. The study reveals APOBEC3 mutagenesis to be a frequent mediator of therapy resistance in breast cancer and highlights its potential as a biomarker and target for overcoming resistance.

eIF4A controls translation of estrogen receptor alpha and is a therapeutic target in advanced breast cancer.

The majority of human breast cancers are dependent on hormone-stimulated estrogen receptor alpha (ER) and are sensitive to its inhibition. Treatment resistance arises in most advanced cancers due to genetic alterations that promote ligand independent activation of ER itself or ER target genes. Whereas re-targeting of the ER ligand binding domain (LBD) with newer ER antagonists can work in some cases, these drugs are largely ineffective in many genetic backgrounds including ER fusions that lose the LBD or in cancers that hyperactivate ER targets. By identifying the mechanism of ER translation, we herein present an alternative strategy to target ER and difficult to treat ER variants. We find that ER translation is cap-independent and mTOR inhibitor insensitive, but dependent on 5' UTR elements and sensitive to pharmacologic inhibition of the translation initiation factor eIF4A, an mRNA helicase. EIF4A inhibition rapidly reduces expression of ER and short-lived targets of ER such as cyclin D1 and other components of the cyclin D-CDK complex in breast cancer cells. These effects translate into suppression of growth of a variety of ligand-independent breast cancer models including those driven by ER fusion proteins that lack the ligand binding site. The efficacy of eIF4A inhibition is enhanced when it is combined with fulvestrant-an ER degrader. Concomitant inhibition of ER synthesis and induction of its degradation causes synergistic and durable inhibition of ER expression and tumor growth. The clinical importance of these findings is confirmed by results of an early clinical trial (NCT04092673) of the selective eIF4A inhibitor zotatifin in patients with estrogen receptor positive metastatic breast cancer. Multiple clinical responses have been observed on combination therapy including durable regressions. These data suggest that eIF4A inhibition could be a useful new strategy for treating advanced ER+ breast cancer.

Optimal systemic treatment and real-world clinical application of ctDNA in patients with metastatic HER2-mutant lung cancer.

INTRODUCTION: No definitive answers currently exist regarding optimal first-line therapy for HER2-mutant NSCLC. Access to rapid tissue sequencing is a major barrier to precision drug development in the first-line setting. ctDNA analysis has the potential to overcome these obstacles and guide treatment. METHODS: We retrospectively analyzed patients with metastatic HER2-mutant NSCLC who underwent prospective clinical ctDNA sequencing and received systemic therapy at Memorial Sloan Kettering Cancer Center (MSK) from January 2016 to September 2022. HER2 mutations were identified by next-generation sequencing through MSK-IMPACT, MSK-ACCESS or Resolution ctDx LungTM assay. Primary endpoints were time to the next treatment (TTNT) and overall survival (OS). RESULTS: Sixty-three patients were included in the primary analysis. Chemoimmunotherapy (33/63, 52.4 %) was the predominant first-line treatment with a median TTNT of 5.1 months (95 %CI 4.1 - 6.1) whereas 55.0 % (22/40) of patients who received second-line T-DXd obtained a median TTNT of 9.2 m (95 % CI, 0-22.2). Plasma ctDNA was tested before first-line therapy in 40 patients with a median OS of 28.0 months (95 % CI 21-34), in whom 31 patients (78.0 %) had detectable ctDNA. HER2 mutations were detected on ctDNA with a median turnaround time of 13 days, occasionally co-occurred with EGFR and MET alterations and were tracked longitudinally correlating with treatment response. Patients with detectable baseline ctDNA had significantly shorter OS (hazard ratio (HR), 5.25; 95 % CI, 1.2-23.9; p = 0.019). CONCLUSION: Chemoimmunotherapy remains a major treatment option for metastatic HER2-mutant NSCLC. ctDNA can rapidly detect HER2 and co-mutations, and it has the potential to guide and monitor optimal first-line therapy. As a negative prognostic biomarker, detectable ctDNA at baseline would need to be taken into account for patient selection in future studies.

A Genomics-Driven Artificial Intelligence-Based Model Classifies Breast Invasive Lobular Carcinoma and Discovers CDH1 Inactivating Mechanisms.

Artificial intelligence (AI)-systems can improve cancer diagnosis, yet their development often relies on subjective histological features as ground truth for training. Here, we developed an AI-model applied to histological whole-slide images (WSIs) using CDH1 bi-allelic mutations, pathognomonic for invasive lobular carcinoma (ILC) in breast neoplasms, as ground truth. The model accurately predicted CDH1 bi-allelic mutations (accuracy=0.95) and diagnosed ILC (accuracy=0.96). A total of 74% of samples classified by the AI-model as having CDH1 bi-allelic mutations but lacking these alterations displayed alternative CDH1 inactivating mechanisms, including a deleterious CDH1 fusion gene and non-coding CDH1 genetic alterations. Analysis of internal and external validation cohorts demonstrated 0.95 and 0.89 accuracy for ILC diagnosis, respectively. The latent features of the AI-model correlated with human-explainable histopathologic features. Taken together, this study reports the construction of an AI-algorithm trained using a genetic rather than histologic ground truth that can robustly classify ILCs and uncover CDH1 inactivating mechanisms, providing the basis for orthogonal ground truth utilization for development of diagnostic AI-models applied to WSI.