COL10A1 expression distinguishes a subset of cancer-associated fibroblasts present in the stroma of high-risk basal cell carcinoma.

BACKGROUND: Basal cell carcinoma (BCC) is the most frequently diagnosed skin cancer and the most common malignancy in humans. Different morphological subtypes of BCC are associated with low- or high-risk of recurrence and aggressiveness, but the underlying biology of how the individual subtypes arise remains largely unknown. Because the majority of BCCs appear to arise from mutations in the same pathway, we hypothesized that BCC development, growth and invasive potential is also influenced by the tumor microenvironment and in particular by cancer-associated fibroblasts (CAFs) and their secreted factors. OBJECTIVE: We aimed to characterize the stroma of the different BCC subtypes with a focus on CAF populations. METHODS: To investigate the stromal features of the different BCC subtypes, we applied laser-capture microdissection (LCM) followed by RNA sequencing. A cohort of 15 BCC samples from 5 different "pure" subtypes (superficial, nodular, micronodular, sclerosing and basosquamous; n=3 each) were selected and included in the analysis. Healthy skin was used as a control (n=6). We confirmed the results by immunohistochemistry. We validated our findings in two independent, public single-cell RNA sequencing (scRNAseq) datasets and by RNAscope. RESULTS: The stroma of the different BCC subtypes have distinct gene expression signatures. Nodular and micronodular seem to have the most similar signatures, while superficial and sclerosing the most different. By comparing low- and high-risk BCC subtypes, we observed that Collagen 10A1 (COL10A1) is overexpressed in the stroma of sclerosing/infiltrative and basosquamous but not micronodular high-risk subtypes. Those findings were confirmed by immunohistochemistry in a cohort of 89 different BCC and 13 healthy skin samples. Moreover, scRNAseq analysis of BCCs of two independent datasets showed that the COL10A1-expressing population of cells is associated with the stroma adjacent to invasive BCC and shows extracellular matrix remodeling features. CONCLUSION: We identified COL10A1 as a marker of high-risk BCC, in particular of the sclerosing/infiltrative and basosquamous subtypes. We demonstrated at the single cell level that COL10A1 is expressed by a specific CAF population associated with the stroma of invasive BCC. This opens up new tailored treatment options as well as a new prognostic biomarker for BCC progression.

LKB1-SIK2 loss drives uveal melanoma proliferation and hypersensitivity to SLC8A1 and ROS inhibition.

Metastatic uveal melanomas are highly resistant to all existing treatments. To address this critical issue, we performed a kinome-wide CRISPR-Cas9 knockout screen, which revealed the LKB1-SIK2 module in restraining uveal melanoma tumorigenesis. Functionally, LKB1 loss enhances proliferation and survival through SIK2 inhibition and upregulation of the sodium/calcium (Na+ /Ca2+ ) exchanger SLC8A1. This signaling cascade promotes increased levels of intracellular calcium and mitochondrial reactive oxygen species, two hallmarks of cancer. We further demonstrate that combination of an SLC8A1 inhibitor and a mitochondria-targeted antioxidant promotes enhanced cell death efficacy in LKB1- and SIK2-negative uveal melanoma cells compared to control cells. Our study also identified an LKB1-loss gene signature for the survival prognostic of patients with uveal melanoma that may be also predictive of response to the therapy combination. Our data thus identify not only metabolic vulnerabilities but also new prognostic markers, thereby providing a therapeutic strategy for particular subtypes of metastatic uveal melanoma.

Combinatorial Treatment with PARP and MAPK Inhibitors Overcomes Phenotype Switch-Driven Drug Resistance in Advanced Melanoma.

Metastatic melanoma is either intrinsically resistant or rapidly acquires resistance to targeted therapy treatments, such as MAPK inhibitors (MAPKi). A leading cause of resistance to targeted therapy is a dynamic transition of melanoma cells from a proliferative to a highly invasive state, a phenomenon called phenotype switching. Mechanisms regulating phenotype switching represent potential targets for improving treatment of patients with melanoma. Using a drug screen targeting chromatin regulators in patient-derived three-dimensional MAPKi-resistant melanoma cell cultures, we discovered that PARP inhibitors (PARPi) restore sensitivity to MAPKis, independent of DNA damage repair pathways. Integrated transcriptomic, proteomic, and epigenomic analyses demonstrated that PARPis induce lysosomal autophagic cell death, accompanied by enhanced mitochondrial lipid metabolism that ultimately increases antigen presentation and sensitivity to T-cell cytotoxicity. Moreover, transcriptomic and epigenetic rearrangements induced by PARP inhibition reversed epithelial-mesenchymal transition-like phenotype switching, which redirected melanoma cells toward a proliferative and MAPKi-sensitive state. The combination of PARP and MAPKis synergistically induced cancer cell death both in vitro and in vivo in patient-derived xenograft models. Therefore, this study provides a scientific rationale for treating patients with melanoma with PARPis in combination with MAPKis to abrogate acquired therapy resistance. SIGNIFICANCE: PARP inhibitors can overcome resistance to MAPK inhibitors by activating autophagic cell death and reversing phenotype switching, suggesting that this synergistic combination could help improve the prognosis of patients with melanoma.

Dynamic thresholding and tissue dissociation optimization for CITE-seq identifies differential surface protein abundance in metastatic melanoma.

Multi-omics profiling by CITE-seq bridges the RNA-protein gap in single-cell analysis but has been largely applied to liquid biopsies. Applying CITE-seq to clinically relevant solid biopsies to characterize healthy tissue and the tumor microenvironment is an essential next step in single-cell translational studies. In this study, gating of cell populations based on their transcriptome signatures for use in cell type-specific ridge plots allowed identification of positive antibody signals and setting of manual thresholds. Next, we compare five skin dissociation protocols by taking into account dissociation efficiency, captured cell type heterogeneity and recovered surface proteome. To assess the effect of enzymatic digestion on transcriptome and epitope expression in immune cell populations, we analyze peripheral blood mononuclear cells (PBMCs) with and without dissociation. To further assess the RNA-protein gap, RNA-protein we perform codetection and correlation analyses on thresholded protein values. Finally, in a proof-of-concept study, using protein abundance analysis on selected surface markers in a cohort of healthy skin, primary, and metastatic melanoma we identify CD56 surface marker expression on metastatic melanoma cells, which was further confirmed by multiplex immunohistochemistry. This work provides practical guidelines for processing and analysis of clinically relevant solid tissue biopsies for biomarker discovery.

Excision repair cross-complementation group 1 protein expression predicts survival in patients with high-grade, non-metastatic osteosarcoma treated with neoadjuvant chemotherapy.

AIMS: To evaluate the clinical impact of excision repair cross-complementation group 1 (ERCC1) expression in high-grade osteosarcoma (OS). METHODS AND RESULTS: Immunohistochemistry was performed on biopsies from 99 OS patients enrolled in the ISG/OS-Oss training set or ISG/SSG1 validation set neoadjuvant chemotherapy protocols, based on the use of cisplatin, adriamycin, methotrexate, and ifosfamide. In the training set, ERCC1 positivity was found in eight of 31 (26%) patients, and was significantly associated with worse event-free survival (EFS) (P = 0.042) and overall survival (OVS) (P = 0.001). In the validation set, ERCC1 positivity was found in 22 of 68 (32%) patients, and its significant associations with poorer EFS (P = 0.028) and OVS (P = 0.022) were confirmed. Multivariate analyses performed on the whole patient series indicated that ERCC1 positivity was the only marker that was significantly associated with a higher risk of worse prognosis, in terms of both EFS and OVS (P = 0.013). Co-evaluation of ERCC1 and ABCB1 expression showed that patients who were positive for both markers had a significantly worse prognosis. CONCLUSIONS: The ERCC1 level at diagnosis is predictive for the outcome of patients with non-metastatic, high-grade OS treated with neoadjuvant chemotherapy, and co-evaluation with ABCB1 can identify high-risk groups of OS patients who are refractory to standard regimens.