A 10-miRNA risk score-based prediction model for pathological complete response to neoadjuvant chemotherapy in hormone receptor-positive breast cancer

Patients with hormone receptor(HR)-positive tumors breast cancer usually experience a relatively low pathological complete response(p CR)to neoadjuvant chemotherapy(NAC).Here,we derived a 10-micro RNA risk score(10-mi RNA RS)-based model with better performance in the prediction of p CR and validated its relation with the disease-free survival(DFS)in 755 HRpositive breast cancer patients(273,265,and 217 in the training,internal,and external validation sets,respectively).This model,presented as a nomogram,included four parameters:the 10-mi RNA RS found in our previous study,progesterone receptor(PR),human epidermal growth factor receptor 2(HER2)status,and volume transfer constant(K).Favorable calibration and discrimination of 10-mi RNA RS-based model with areas under the curve(AUC)of 0.865,0.811,and 0.804 were shown in the training,internal,and external validation sets,respectively.Patients who have higher nomogram score(>92.2)with NAC treatment would have longer DFS(hazard ratio=0.57;95%CI:0.39–0.83;P=0.004).In summary,our data showed the 10-mi RNA RS-based model could precisely identify more patients who can attain p CR to NAC,which may help clinicians formulate the personalized initial treatment strategy and consequently achieves better clinical prognosis for patients with HRpositive breast cancer.

Targeting DNA repair pathways to overcome cancer drug resistance

DNA damage response and DNA repair pathways are evolutionarily conserved from prokaryotes to eukaryotes to protect the host from genomic instability.Dysregulation of proteins involved in these pathways in mammalian cells increases genomic alterations leading to genomic instability,a well-established hallmark of cancer^([1,2]).However,our understanding of the signaling pathways to repair DNA damage in cancers has grown exponentially over the last decades.

Predictive biomarkers for immune checkpoint blockade and opportunities for combination therapies

Immune checkpoint blockade therapies(ICBs)are a prominent breakthrough in cancer immunotherapy in recent years(named the 2013“Breakthrough of the Year”by the Science magazine).Thus far,FDA-approved ICBs primarily target immune checkpoints CTLA-4,PD-1,and PD-L1.Notwithstanding their impressive long-term therapeutic benefits,their efficacy is limited to a small subset of cancer patients.In addition,ICBs induce inadvertent immune-related adverse events(irAEs)and can be costly for long-term use.To overcome these limitations,two strategies are actively being pursued:identification of predictive biomarkers for clinical response to ICBs and multi-pronged combination therapies.Biomarkers will allow clinicians to practice a precision medicine approach in ICBs(biomarker-based patient selection)such as treating triple-negative breast cancer patients that exhibit PD-L1 staining of tumor-infiltrating immune cells in
1%of the tumor area with nanoparticle albumin-bound(nab)epaclitaxel plus anti-PD-L1 and treating patients of MSI-H or MMR deficient unresectable or metastatic solid tumors with pembrolizumab(anti-PD-1).Importantly,the insights gained from these biomarker studies can guide rational combinatorial strategies such as CDK4/6 inhibitor/fractionated radiotherapy/HDACi in conjunction with ICBs to maximize therapeutic benefits.Further,with the rapid technological advents(e.g.,ATCT-Seq),we predict more reliable biomarkers will be identified,which in turn will inspire more promising combination therapies.