Extracellular Matrix Features Discriminate Aggressive HER2-Positive Breast Cancer Patients Who Benefit from Trastuzumab Treatment

Combining the tumor-stroma ratio with tumor-infiltrating lymphocytes improves the prediction of pathological complete response in breast cancer patients

PURPOSE

The tumor-stroma ratio (TSR) is a common histological parameter that measures stromal abundance and is prognostic in breast cancer (BC). However, more evidence is needed on the predictive value of the TSR for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). The purpose of this study was to determine the importance of the TSR in predicting pCR in NAC settings.

METHOD

We evaluated the TSR on pretreatment biopsies of 912 BC patients from four independent Chinese hospitals and investigated the potential value of the TSR for predicting pCR. Meanwhile, stromal tumor-infiltrating lymphocytes (sTILs) were assessed, and we evaluated the predictive value of the combination of sTILs and TSR (TSRILs).

RESULTS

Patients with low stroma showed a higher pCR rate than those with high stroma among the four independent hospitals, and in multivariate analysis, the TSR was proven to be an independent predictor for pCR to NAC with an odds ratio of 1.945 (95% CI 1.230-3.075, P = 0.004). Moreover, we found that TSRILs could improve the area under the curve (AUC) for predicting pCR from 0.750 to 0.785 (P = 0.039); especially in HER2-negative BCs, the inclusion of TSRILs increased the AUC from 0.801 to 0.835 in the discovery dataset (P = 0.048) and 0.734 to 0.801 in the validation dataset (P = 0.003).

CONCLUSION

TSR and sTILs can be easily measured in pathological routines and provide predictive information without additional cost; with more evidence from clinical trials, TSRILs could be a candidate to better stratify patients in NAC settings.

Identification and validation of an autophagy-related signature for predicting survival in lower-grade glioma

Abnormal levels of autophagy have been implicated in the pathogenesis of multiple diseases, including cancer. However, little is known about the role of autophagy-related genes (ARGs) in low-grade gliomas (LGG). Accordingly, the aims of this study were to assess the prognostic values of ARGs and to establish a genetic signature for LGG prognosis. Expression profile data from patients with and without primary LGG were obtained from The Cancer Genome Atlas (TCGA) and Genome Tissue Expression databases, respectively, and consensus clustering was used to identify clusters of patients with distinct prognoses. Nineteen differentially expressed ARGs were selected with threshold values of FDR < 0.05 and |log2 fold change (FC)| ≥ 2, and functional analysis revealed that these genes were associated with autophagy processes as expected. An autophagy-related signature was established using a Cox regression model of six ARGs that separated patients from TCGA training cohort into high- and low-risk groups. Univariate and multivariate Cox regression analysis indicated that the signature-based risk score was an independent prognostic factor. The signature was successfully validated using the TCGA testing, TCGA entire, and Chinese Glioma Genome Atlas cohorts. Stratified analyses demonstrated that the signature was associated with clinical features and prognosis, and gene set enrichment analysis revealed that autophagy- and cancer-related pathways were more enriched in high-risk patients than in low-risk patients. The prognostic value and expression of the six signature-related genes were also investigated. Thus, the present study constructed and validated an autophagy-related prognostic signature that could optimize individualized survival prediction in LGG patients.

Targeting Discoidin Domain Receptor 1 (DDR1) Signaling and Its Crosstalk with β1-integrin Emerges as a Key Factor for Breast Cancer Chemosensitization upon Collagen Type 1 Binding

Collagen type 1 (COL1) is a ubiquitously existing extracellular matrix protein whose high density in breast tissue favors metastasis and chemoresistance. COL1-binding of MDA-MB-231 and MCF-7 breast cancer cells is mainly dependent on β₁-integrins (ITGB1). Here, we elucidate the signaling of chemoresistance in both cell lines and their ITGB1-knockdown mutants and elucidated MAPK pathway to be strongly upregulated upon COL1 binding. Notably, Discoidin Domain Receptor 1 (DDR1) was identified as another important COL1-sensor, which is permanently active but takes over the role of COL1-receptor maintaining MAPK activation in ITGB1-knockdown cells. Consequently, inhibition of DDR1 and ERK1/2 act synergistically, and sensitize the cells for cytostatic treatments using mitoxantrone, or doxorubicin, which was associated with an impaired ABCG2 drug efflux transporter activity. These data favor DDR1 as a promising target for cancer cell sensitization, most likely in combination with MAPK pathway inhibitors to circumvent COL1 induced transporter resistance axis. Since ITGB1-knockdown also induces upregulation of pEGFR in MDA-MB-231 cells, inhibitory approaches including EGFR inhibitors, such as gefitinib appear promising for pharmacological interference. These findings provide evidence for the highly dynamic adaptation of breast cancer cells in maintaining matrix binding to circumvent cytotoxicity and highlight DDR1 signaling as a target for sensitization approaches.