Metformin has been reported to possess antitumor activity and maintain high cytotoxic T lymphocyte (CTL) immune surveillance. However, the functions and detailed mechanisms of metformin's role in cancer immunity are not fully understood. Here, we show that metformin increases CTL activity by reducing the stability and membrane localization of programmed death ligand-1 (PD-L1). Furthermore, we discover that AMP-activated protein kinase (AMPK) activated by metformin directly phosphorylates S195 of PD-L1. S195 phosphorylation induces abnormal PD-L1 glycosylation, resulting in its ER accumulation and ER-associated protein degradation (ERAD). Consistently, tumor tissues from metformin-treated breast cancer patients exhibit reduced PD-L1 levels with AMPK activation. Blocking the inhibitory signal of PD-L1 by metformin enhances CTL activity against cancer cells. Our findings identify a new regulatory mechanism of PD-L1 expression through the ERAD pathway and suggest that the metformin-CTLA4 blockade combination has the potential to increase the efficacy of immunotherapy.

AIMTo investigate the clinical significance of preoperative systemic immune-inflammation index (SII) in patients with colorectal cancer (CRC).METHODSA retrospective analysis of 1383 cases with CRC was performed following radical surgery. SII was calculated with the formula SII = (P × N)/L, where P, N, and L refer to peripheral platelet, neutrophil, and lymphocyte counts, respectively. The clinicopathological features and follow-up data were evaluated to compare SII with other systemic inflammation-based prognostic indices such as the neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in patients with CRC.RESULTSThe optimal cut-off point for SII was defined as 340. The overall survival (OS) and disease-free survival (DFS) were better in patients with low NLR, PLR, and SII (P < 0.05). The SII was an independent predictor of OS and DFS in multivariate analysis. The area under the receiver-operating characteristics (ROC) curve for SII (0.707) was larger than those for NLR (0.602) and PLR (0.566). In contrast to NLR and PLR, SII could effectively discriminate between the TNM subgroups.CONCLUSIONSII is a more powerful tool for predicting survival outcome in patients with CRC. It might assist the identification of high-risk patients among patients with the same TNM stage.

Eradicating triple negative breast cancer (TNBC) resistant to neoadjuvant chemotherapy (NACT) is a critical unmet clinical need. In this study, patient-derived xenograft (PDX) models of treatment-naïve TNBC and serial biopsies from TNBC patients undergoing NACT were used to elucidate mechanisms of chemoresistance in the neoadjuvant setting. Barcode-mediated clonal tracking and genomic sequencing of PDX tumors revealed that residual tumors remaining after treatment with standard front-line chemotherapies, doxorubicin (Adriamycin) combined with cyclophosphamide (AC), maintained the subclonal architecture of untreated tumors yet their transcriptomes, proteomes, and histologic features were distinct from those of untreated tumors. Once treatment was halted, residual tumors gave rise to AC-sensitive tumors with similar transcriptomes, proteomes, and histological features to those of untreated tumors. Taken together, these results demonstrated that tumors can adopt a reversible drug-tolerant state that does not involve clonal selection as an AC resistance mechanism. Serial biopsies obtained from patients with TNBC undergoing NACT revealed similar histologic changes as well as maintenance of stable subclonal architecture, demonstrating that AC-treated PDXs capture molecular features characteristic of human TNBC chemoresistance. Finally, pharmacologic inhibition of oxidative phosphorylation using an inhibitor currently in phase I clinical development delayed residual tumor regrowth. Thus, AC resistance in treatment-naïve TNBC can be mediated by non-selective mechanisms that confer a reversible chemotherapy-tolerant state with targetable vulnerabilities.

Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational pre-clinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and “Triple-negative” (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward “credentialing” of PDX models as surrogates to represent individual patients for use in pre-clinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research.

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