Project description:Although high clinical response rates are seen for immune checkpoint blockade (ICB) of metastatic melanoma, both intrinsic and acquired ICB resistance remain formidable challenges. Combination ICB shows improved clinical benefit, but is associated with severe adverse events and exceedingly high cost. Therefore, there is a dire need to stratify individual patients for their likelihood of responding to either anti-PD-1 or anti-CTLA-4 monotherapy, or the combination. Since it is conceivable that ICB responses are influenced by both tumor cell-intrinsic and stromal factors, we hypothesized that a predictive classifier ought to mirror both of these distinct features. We used a panel of melanoma patient-derived xenografts (PDX), in which human stromal cells upon transplantation are naturally replaced by their murine counterparts, to computationally subtract PDX RNA expression signals from those in patients’ melanomas. We thus derived both “Stromal immune” (SIM) and tumor cell-specific “Tumor-autonomous inflammation” (TAF) signatures. Here we report that the SIM signature predicts response to anti-CTLA-4 but not anti-PD-1 treatment, whereas the tumor TAF signature predicts response to anti-PD-1 but not anti-CTLA-4. Moreover, when used in conjunction, the signatures accurately predict response in two independent patient cohorts treated with the anti-CTLA-4 + anti-PD-1 combination. These signatures may be clinically exploited for personalized treatment advice based on the predicted benefit from either anti-CTLA-4 or anti-PD-1 monotherapy or their combination.

2020-04-27 | GSE129127 | GEO

Patient-derived xenograft platform for metastatic melanoma: RNA sequencing of 4 melanoma PDX samples

Project description:The therapeutic landscape of melanoma is rapidly changing. While targeted inhibitors yield significant responses, their clinical benefit is often limited by the early onset of drug resistance. This motivates the pursuit to establish more durable clinical responses, by developing combinatorial therapies. But while potential new combinatorial targets steadily increase in numbers, they cannot possibly all be tested in patients. Similarly, while genetically engineered mouse melanoma models have great merit, they do not capture the enormous genetic diversity and heterogeneity typical in human melanoma. Furthermore, whereas in vitro studies have many advantages, they lack the presence of micro-environmental factors, which can have a profound impact on tumor progression and therapy response. This prompted us to develop an in vivo model for human melanoma that allows for studying the dynamics of tumor progression and drug response, with concurrent evaluation and optimization of new treatment regimens. Here, we present a collection of patient-derived xenografts (PDX), derived from BRAFV600E, NRASQ61 or BRAFWT/NRASWT melanoma metastases. The BRAFV600E PDX melanomas were acquired both prior to treatment with the BRAF inhibitor vemurafenib and after resistance had occurred, including six matched pairs. We find that PDX resemble their human donors’ melanomas regarding biomarkers, chromosomal aberrations, RNA expression profiles, mutational spectrum and targeted drug resistance patterns. Mutations, previously identified to cause resistance to BRAF inhibitors, are captured in PDX derived from resistant melanomThis melanoma PDX platform represents a comprehensive public resource to study both fundamental and translational aspects of melanoma progression and treatment in a physiologically relevant setting.

2016-05-27 | GSE73737 | GEO

Conjunctival Melanoma in Childhood and Adolescence: A Systematic Review.

Project description: Not available

| S-EPMC6873081 | biostudies-literature

Childhood sunburn and risk of melanoma and non-melanoma skin cancer: a Mendelian randomization study.

Project description: Not available

| S-EPMC10724097 | biostudies-literature

[SJCRH] [PDX] [SJOS030876_X2] Childhood Osteosarcoma

Project description: Not available

| S-CMO2304 | biostudies-other