Biomarker predictors for immunotherapy benefit in breast: beyond PD-L1

Epithelial Expressed B7-H4 Drives Differential Immunotherapy Response in Murine and Human Breast Cancer

Combinations of immune checkpoint inhibitors (ICI, including anti-PD-1/PD-L1) and chemotherapy have been FDA approved for metastatic and early-stage triple-negative breast cancer (TNBC), but most patients do not benefit. B7-H4 is a B7 family ligand with proposed immunosuppressive functions being explored as a cancer immunotherapy target and may be associated with anti-PD-L1 resistance. However, little is known about its regulation and effect on immune cell function in breast cancers. We assessed murine and human breast cancer cells to identify regulation mechanisms of B7-H4 in vitro. We used an immunocompetent anti-PD-L1-sensitive orthotopic mammary cancer model and induced ectopic expression of B7-H4. We assessed therapy response and transcriptional changes at baseline and under treatment with anti-PD-L1. We observed B7-H4 was highly associated with epithelial cell status and transcription factors and found to be regulated by PI3K activity. EMT6 tumors with cell-surface B7-H4 expression were more resistant to immunotherapy. In addition, tumor-infiltrating immune cells had reduced immune activation signaling based on transcriptomic analysis. Paradoxically, in human breast cancer, B7-H4 expression was associated with survival benefit for patients with metastatic TNBC treated with carboplatin plus anti-PD-L1 and was associated with no change in response or survival for patients with early breast cancer receiving chemotherapy plus anti-PD-1. While B7-H4 induces tumor resistance to anti-PD-L1 in murine models, there are alternative mechanisms of signaling and function in human cancers. In addition, the strong correlation of B7-H4 to epithelial cell markers suggests a potential regulatory mechanism of B7-H4 independent of PD-L1.

SIGNIFICANCE

This translational study confirms the association of B7-H4 expression with a cold immune microenvironment in breast cancer and offers preclinical studies demonstrating a potential role for B7-H4 in suppressing response to checkpoint therapy. However, analysis of two clinical trials with checkpoint inhibitors in the early and metastatic settings argue against B7-H4 as being a mechanism of clinical resistance to checkpoints, with clear implications for its candidacy as a therapeutic target.

Genomic alteration profile and PD-L1 expression among different breast cancer subtypes in Chinese population and their correlations

BACKGROUD

There were limitations existing in programmed cell-death ligand 1 (PD-L1) as predictive biomarkers for breast cancer (BC), hence exploring the correlation between PD-L1 levels and other biomarkers in BC may become a very useful therapeutic clinical tool.

METHODS

A total of 301 Chinese patients with different BC subtypes including 47 HR+/HER2+, 185 HR+/HER2-, 38 HR-/HER2+, and 31 triple-negative breast cancer (TNBC) were enrolled in our study. Next-generation sequencing based Yuansu450 gene panel was used for genomic alteration identification and PD-L1 expression was tested using immunohistochemistry.

RESULTS

The most prevalent BC-related mutations were TP53 mutations, followed by mutations in PIK3CA, ERBB2, CDK12, and GATA3 in our Chinese cohort. We found that mutations DDR2 and MYCL were only mutated in HR-/HER2+ subtype, whereas H3-3A and NRAS mutations were only occurred in HR-/HER2- subtype. The percentage of patients with PD-L1-positive expression was higher in patients with HR-/HER2- mainly due to the percentage of PD-L1-high level. Mutational frequencies of TP53, MYC, FAT4, PBRM1, PREX2 were observed to have significant differences among patients with different BC subtypes based on PD-L1 levels. Moreover, a positive correlation was observed between TMB and PD-L1 level in HR+/HER2- subtype, and showed that the proportion of patients with high PD-L1 expression was higher than that of patients with low PD-L1 expression in the HR+/HER2- and HR+/HER2+ cohorts with high Ki67 expression.

CONCLUSIONS

The genomic alterations based on PD-L1 and other biomarkers of different cohorts may provide more possibilities for the treatment of BC with different subtypes.

Automated detection of vascular remodeling in tumor-draining lymph nodes by the deep learning tool HEV-finder

Vascular remodeling is common in human cancer and has potential as future biomarkers for prediction of disease progression and tumor immunity status. It can also affect metastatic sites, including the tumor‐draining lymph nodes (TDLNs). Dilation of the high endothelial venules (HEVs) within TDLNs has been observed in several types of cancer. We recently demonstrated that it is a premetastatic effect that can be linked to tumor invasiveness in breast cancer. Manual visual assessment of changes in vascular morphology is a tedious and difficult task, limiting high‐throughput analysis. Here we present a fully automated approach for detection and classification of HEV dilation. By using 12,524 manually classified HEVs, we trained a deep‐learning model and created a graphical user interface for visualization of the results. The tool, named the HEV‐finder, selectively analyses HEV dilation in specific regions of the lymph nodes. We evaluated the HEV‐finder's ability to detect and classify HEV dilation in different types of breast cancer compared to manual annotations. Our results constitute a successful example of large‐scale, fully automated, and user‐independent, image‐based quantitative assessment of vascular remodeling in human pathology and lay the ground for future exploration of HEV dilation in TDLNs as a biomarker. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Potential Predictive and Prognostic Value of Biomarkers Related to Immune Checkpoint Inhibitor Therapy of Triple-Negative Breast Cancer

As an aggressive subtype of breast cancer, triple-negative breast cancer (TNBC) is associated with poor prognosis and lack of effective therapy, except chemotherapy. In recent years, immunotherapy based on immune checkpoint (IC) inhibition has emerged as a promising therapeutic strategy in TNBC. TNBC has more tumor-infiltrating lymphocytes (TILs) and higher rate of mutation and programmed cell death ligand-1 (PD-L1) expression than other subtypes of breast cancer have. However, previous studies have shown that monotherapy has little efficacy and only some TNBC patients can benefit from immunotherapy. Therefore, it is important to identify biomarkers that can predict the efficacy of IC inhibitors (ICIs) in TNBC. Recently, various biomarkers have been extensively explored, such as PD-L1, TILs and tumor mutational burden (TMB). Clinical trials have shown that PD-L1-positive patients with advanced TNBC benefit from ICIs plus chemotherapy. However, in patients with early TNBC receiving neoadjuvant therapy, PD-L1 cannot predict the efficacy of ICIs. These inconsistent conclusions suggest that PD-L1 is the best to date but an imperfect predictive biomarker for efficacy of ICIs. Other studies have shown that advanced TNBC patients with TMB ≥10 mutations/Mb can achieve clinical benefits from pembrolizumab. TILs also have potential predictive value in TNBC. Here, we select some biomarkers related to ICIs and discuss their potential predictive and prognostic value in TNBC. We hope these biomarkers could help to identify suitable patients and realize precision immunotherapy.

A risk scoring system based on tumor microenvironment cells to predict prognosis and immune activity in triple-negative breast cancer

The tumor microenvironment (TME) interacting with the malignant cells plays a vital role in cancer development. Herein, we aim to establish and verify a scoring system based on the characteristics of TME cells for prognosis prediction and personalized treatment guidance in patients with triple-negative breast cancer (TNBC). 158 TNBC samples from The Cancer Genome Atlas (TCGA) were included as the training cohort, and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), as well as GSE58812 (N = 107), were included as the validation cohort. The enrichment scores of 64 immune and stromal cells were estimated by the xCell algorithm. In the training cohort, cells with prognostic significance were found out using univariate Cox regression analysis and further applied to the random survival forest (RSF) model. Based on the scores of M2 macrophages, CD8+ T cells, and CD4+ memory T cells, a risk scoring system was constructed, which divided TNBC patients into 4 phenotypes (M2low, M2highCD8+ThighCD4+Thigh, M2highCD8+ThighCD4+Tlow, and M2highCD8+Tlow). Furthermore, types 1 and 2 patients were merged into the low-risk group, while types 3 and 4 patients were in the high-risk group. The low-risk group had superior survival outcomes than the high-risk one, which was further confirmed in the validation cohort. Moreover, in the low-risk group, immune-related pathways were significantly enriched, and a higher level of antitumoral immune cells and immune checkpoint molecules, including PD-L1, PD-1, and CTLA-4, could be observed. Additionally, consistent results were achieved in the SYSUCC cohort when the scoring system was applied. In summary, this novel scoring system might predict the survival and immune activity of patients and might serve as a potential index for immunotherapy.

Efficacy of Rac and Cdc42 Inhibitor MBQ-167 in Triple-negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive form of breast cancer, with a high predisposition for locally invasive and metastatic cancer. With the objective to reduce cancer metastasis, we developed small molecule inhibitors to target the drivers of metastasis, the Rho GTPases Rac and Cdc42. Of these, MBQ-167 inhibits both Rac and Cdc42 with IC50s of 103 and 78 nmol/L, respectively; and consequently, inhibits p21-activated kinase (PAK) signaling, metastatic cancer cell proliferation, migration, and mammosphere growth; induces cell-cycle arrest and apoptosis; and decreases HER2-type mammary fatpad tumor growth and metastasis (Humphries-Bickley and colleagues, 2017). Herein, we used nuclear magnetic resonance to show that MBQ-167 directly interacts with Rac1 to displace specific amino acids, and consequently inhibits Rac.GTP loading and viability in TNBC cell lines. Phosphokinome arrays in the MDA-MB-231 human TNBC cells show that phosphorylation status of kinases independent of the Rac/Cdc42/PAK pathway are not significantly changed following 200 nmol/L MBQ-167 treatment. Western blotting shows that initial increases in phospho-c-Jun and phospho-CREB in response to MBQ-167 are not sustained with prolonged exposure, as also confirmed by a decrease in their transcriptional targets. MBQ-167 inhibits tumor growth, and spontaneous and experimental metastasis in immunocompromised (human TNBC) and immunocompetent (mouse TNBC) models. Moreover, per oral administration of MBQ-167 at 100 mg/kg body weight is not toxic to immunocompetent BALB/c mice and has a half-life of 4.6 hours in plasma. These results highlight the specificity, potency, and bioavailability of MBQ-167, and support its clinical potential as a TNBC therapeutic.

Early memory differentiation and cell death resistance in T cells predicts melanoma response to sequential anti-CTLA4 and anti-PD1 immunotherapy

Immune checkpoint blockers (ICBs)-based immunotherapy has revolutionised oncology. However, the benefits of ICBs are limited to only a subset of patients. Herein, the biomarkers-driven application of ICBs promises to increase their efficacy. Such biomarkers include lymphocytic IFNγ-signalling and/or cytolytic activity (granzymes and perforin-1) footprints, whose levels in pre-treatment tumours can predict favourable patient survival following ICB-treatment. However, it is not clear whether such biomarkers have the same value in predicting survival of patients receiving first-line anti-CTLA4 ICB-therapy, and subsequently anti-PD1 ICB-therapy (i.e., sequential ICB-immunotherapy regimen). To address this, we applied highly integrated systems/computational immunology approaches to existing melanoma bulk-tumour transcriptomic and single-cell (sc)RNAseq data originating from immuno-oncology clinical studies applying ICB-treatment. Interestingly, we observed that CD8⁺/CD4⁺T cell-associated IFNγ-signalling or cytolytic activity signatures fail to predict tumour response in patients treated with anti-CTLA4 ICB-therapy as a first-line and anti-PD1 ICB-therapy in the second-line setting. On the contrary, signatures associated with early memory CD8⁺/CD4⁺T cells (integrating TCF1-driven stem-like transcriptional programme), capable of resisting cell death/apoptosis, better predicted objective response rates to ICB-immunotherapy, and favourable survival in the setting of sequential ICB-immunotherapy. These observations suggest that sequencing of ICB-therapy might have a specific impact on the T cell-repertoire and may influence the predictive value of tumoural immune biomarkers.