Abstract PD14-07: Association between biomarkers and response to pembrolizumab in patients with metastatic triple-negative breast cancer (mTNBC): Exploratory analysis from KEYNOTE-086

Evolving Management of Breast Cancer in the Era of Predictive Biomarkers and Precision Medicine

Breast cancer is the most common cancer among women in the world as well as in the United States. Molecular and histological differentiation have helped clinicians optimize treatments with various therapeutics, including hormonal therapy, chemotherapy, immunotherapy, and radiation therapy. Recently, immunotherapy has become the standard of care in locally advanced triple-negative breast cancer and an option across molecular subtypes for tumors with a high tumor mutation burden. Despite the advancements in personalized medicine directing the management of localized and advanced breast cancers, the emergence of resistance to these therapies is the leading cause of death among breast cancer patients. Therefore, there is a critical need to identify and validate predictive biomarkers to direct treatment selection, identify potential responders, and detect emerging resistance to standard therapies. Areas of active scientific and clinical research include novel personalized and predictive biomarkers incorporating tumor microenvironment, tumor immune profiling, molecular characterization, and histopathological differentiation to predict response and the potential emergence of resistance.

Predictive biomarkers of response and survival following immunotherapy with a PD-L1 inhibitor benmelstobart (TQB2450) and antiangiogenic therapy with a VEGFR inhibitor anlotinib for pretreated advanced triple negative breast cancer

In our phase Ib trial (ClinialTrials.gov Identifier: NCT03855358), benmelstobart (TQB2450), a novel humanized IgG1 antibody against PD-L1, plus antiangiogenic multikinase inhibitor, anlotinib, demonstrated promising antitumor activities in pretreated triple negative breast cancer (TNBC) patients. We conducted explorative analyses of genomic biomarkers to explore the associations with treatment response and survival outcomes. Targeted next generation sequencing (NGS) was undertaken toward circulating tumor DNA (ctDNA) collected from peripheral blood samples prior to the start of treatment and after disease progression. A total of 31 patients received targeted NGS and functional driver mutations in 29 patients were analyzed. The most frequent mutations were TP53 (72%), MLL3 (28%), and PIK3CA (17%). At a blood-based tumor mutational burden (bTMB) cutoff of 6.7 mutations per megabase, patients with low bTMB showed better response to anlotinib plus TQB2450 (50% vs. 7%, P = 0.015) and gained greater PFS benefits (7.3 vs. 4.1 months, P = 0.012) than those with high bTMB. At a maximum somatic allele frequency (MSAF) cutoff of 10%, a low MSAF indicated a better objective response (43% vs. 20%) as well as a significantly longer median PFS (7.9 vs. 2.7 months, P < 0.001). Patients with both low MSAF and low bTMB showed a notably better objective response to anlotinib plus TQB2450 (70% vs. 11%, P < 0.001) and a significantly longer median PFS (11.0 vs. 2.9 months, P < 0.001) than patients with other scenarios. Our findings support future studes and validation of MSAF and the combined bTMB-MSAF classification as predictive biomarkers of immune checkpoint inhibitor-based regimens in advanced TNBC patients.

Tissue- and liquid biopsy-based biomarkers for immunotherapy in breast cancer

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and now represent the mainstay of treatment for many tumor types, including triple-negative breast cancer and two agnostic registrations. However, despite impressive durable responses suggestive of an even curative potential in some cases, most patients receiving ICIs do not derive a substantial benefit, highlighting the need for more precise patient selection and stratification. The identification of predictive biomarkers of response to ICIs may play a pivotal role in optimizing the therapeutic use of such compounds. In this Review, we describe the current landscape of tissue and blood biomarkers that could serve as predictive factors for ICI treatment in breast cancer. The integration of these biomarkers in a "holistic" perspective aimed at developing comprehensive panels of multiple predictive factors will be a major step forward towards precision immune-oncology.

Immunotherapy in breast cancer: an overview of current strategies and perspectives

Recent progress in immunobiology has led the way to successful host immunity enhancement against breast cancer. In triple-negative breast cancer, the combination of cancer immunotherapy based on PD-1/PD-L1 immune checkpoint inhibitors with chemotherapy was effective both in advanced and early setting phase 3 clinical trials. These encouraging results lead to the first approvals of immune checkpoint inhibitors in triple-negative breast cancer and thus offer new therapeutic possibilities in aggressive tumors and hard-to-treat populations. Furthermore, several ongoing trials are investigating combining immunotherapies involving immune checkpoint inhibitors with conventional therapies and as well as with other immunotherapeutic strategies such as cancer vaccines, CAR-T cells, bispecific antibodies, and oncolytic viruses in all breast cancer subtypes. This review provides an overview of immunotherapies currently under clinical development and updated key results from clinical trials. Finally, we discuss the challenges to the successful implementation of immune treatment in managing breast cancer and their implications for the design of future clinical trials.

Predictive Biomarkers for Response to Immunotherapy in Triple Negative Breast Cancer: Promises and Challenges

Triple negative breast cancer (TNBC) is a highly heterogeneous disease with a poor prognosis and a paucity of therapeutic options. In recent years, immunotherapy has emerged as a new treatment option for patients with TNBC. However, this therapeutic evolution is paralleled by a growing need for biomarkers which allow for a better selection of patients who are most likely to benefit from this immune checkpoint inhibitor (ICI)-based regimen. These biomarkers will not only facilitate a better optimization of treatment strategies, but they will also avoid unnecessary side effects in non-responders, and limit the increasing financial toxicity linked to the use of these agents. Huge efforts have been deployed to identify predictive biomarkers for the ICI, but until now, the fruits of this labor remained largely unsatisfactory. Among clinically validated biomarkers, only programmed death-ligand 1 protein (PD-L1) expression has been prospectively assessed in TNBC trials. In addition to this, microsatellite instability and a high tumor mutational burden are approved as tumor agnostic biomarkers, but only a small percentage of TNBC fits this category. Furthermore, TNBC should no longer be approached as a single biological entity, but rather as a complex disease with different molecular, clinicopathological, and tumor microenvironment subgroups. This review provides an overview of the validated and evolving predictive biomarkers for a response to ICI in TNBC.

Multiplexed In Situ Spatial Protein Profiling in the Pursuit of Precision Immuno-Oncology for Patients with Breast Cancer

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many solid tumors. In breast cancer (BC), immunotherapy is currently approved in combination with chemotherapy, albeit only in triple-negative breast cancer. Unfortunately, most patients only derive limited benefit from ICIs, progressing either upfront or after an initial response. Therapeutics must engage with a heterogeneous network of complex stromal-cancer interactions that can fail at imposing cancer immune control in multiple domains, such as in the genomic, epigenomic, transcriptomic, proteomic, and metabolomic domains. To overcome these types of heterogeneous resistance phenotypes, several combinatorial strategies are underway. Still, they can be predicted to be effective only in the subgroups of patients in which those specific resistance mechanisms are effectively in place. As single biomarker predictive performances are necessarily suboptimal at capturing the complexity of this articulate network, precision immune-oncology calls for multi-omics tumor microenvironment profiling in order to identify unique predictive patterns and to proactively tailor combinatorial treatments. Multiplexed single-cell spatially resolved tissue analysis, through precise epitope colocalization, allows one to infer cellular functional states in view of their spatial organization. In this review, we discuss-through the lens of the cancer-immunity cycle-selected, established, and emerging markers that may be evaluated in multiplexed spatial protein panels to help identify prognostic and predictive patterns in BC.

Current Treatment and Future Trends of Immunotherapy in Breast Cancer

Immunotherapy continues to redefine the solid tumor treatment landscape with inhibitors of the PD-L1/PD-1 immune checkpoint having the most widespread impact. As the most common cancer diagnosed worldwide, there is significant interest in the development of immunotherapy for the treatment of breast cancer in both the early and metastatic settings. Recently reported results of several clinical trials have identified potential roles for immunotherapy agents alone or in combination with standard treatment for early and metastatic disease. While trials to date have been promising, immunotherapy thus far has been shown to benefit only a select group of patients with breast cancer, defined by tumor subtype, PD-L1 expression, and line of therapy. With over 250 trials ongoing, emerging data will enable the further refinement of breast cancer immunotherapy strategies. The integration of multiple putative biomarkers and consideration of dynamic markers of early response or resistance may inform optimal patient selection for immunotherapy investigation and integration into clinical practice. This review will summarize the current evidence for immune-checkpoint blockade (ICB) in the treatment of early and metastatic breast cancer and highlight current and potential future biomarkers of therapeutic response.

Predictive Biomarkers of Immune Checkpoint Inhibitor Response in Breast Cancer: Looking beyond Tumoral PD-L1

Immune checkpoint inhibitors utilize the immune system to kill cancer cells and are now widely applied across numerous malignancies. Pembrolizumab has two breast-specific indications in triple-negative disease. Currently, programmed death ligand-1 (PD-L1) expression on tumor and surrounding immune cells is the only validated predictive biomarker for immune checkpoint inhibitors (ICIs) in breast cancer; however, it can be imprecise. Additional biomarkers are needed to identify the patient population who will derive the most benefit from these therapies. The tumor immune microenvironment contains many biomarker candidates. In tumor cells, tumor mutational burden has emerged as a robust biomarker across malignancies in general, with higher burden cancers demonstrating improved response, but will need further refinement for less mutated cancers. Preliminary studies suggest that mutations in breast cancer gene 2 (BRCA-2) are associated with increased immune infiltration and response to ICI therapy. Other genomic alterations are also being investigated as potential predictive biomarkers. In immune cells, increased quantity of tumor-infiltrating lymphocytes and CD8+ cytotoxic T cells have correlated with response to immunotherapy treatment. The role of other immune cell phenotypes is being investigated. Peripherally, many liquid-based biomarker strategies such as PD-L1 expression on circulating tumor cells and peripheral immune cell quantification are being studied; however, these strategies require further standardization and refinement prior to large-scale testing. Ultimately, multiple biomarkers utilized together may be needed to best identify the appropriate patients for these treatments.

Seeing the forest and the tree: TILs and PD-L1 as immune biomarkers

Here we will provide an immune-focussed overview of biomarkers in early and advanced stage breast cancer. It should be noted from the outset that all the biomarkers under discussion here have not been tested in prospective clinical trials to determine their predictive performance. Such trials require very large sample sizes due to the statistical burden of testing an interaction between a treatment and a biomarker, which is compounded by the heterogeneous biology of breast cancer (Polley et al. in J Natl Cancer Inst 105:1677-1683 2013 [1]). For a detailed discussion of the immunobiology of breast cancer, analytical aspects of these biomarkers, emerging biomarkers such as tumour mutation burden and detailed immunotherapy clinical trial data, see other articles in this issue.