Penile squamous cell carcinoma (PSCC) is a rare malignancy in most parts of the world and the underlying mechanisms of this disease have not been fully investigated. About 30–50% of cases are associated with high-risk human papillomavirus (HPV) infection, which may have prognostic value. When PSCC becomes resistant to upfront therapies there are limited options, thus further research is needed in this venue. The extracellular domain-facing protein profile on the cell surface (i.e., the surfaceome) is a key area for biomarker and drug target discovery. This research employs computational methods combined with cell line translatomic (n = 5) and RNA-seq transcriptomic data from patient-derived tumors (n = 18) to characterize the PSCC surfaceome, evaluate the composition dependency on HPV infection, and explore the prognostic impact of identified surfaceome candidates. Immunohistochemistry (IHC) was used to validate the localization of select surfaceome markers. This analysis characterized a diverse surfaceome within patient tumors with 25% and 18% of the surfaceome represented by the functional classes of receptors and transporters, respectively. Significant differences in protein classes were noted by HPV status, with the most change being seen in transporter proteins (25%). IHC confirmed the robust surface expression of select surfaceome targets in the top 85% of expression and a superfamily immunoglobulin protein called BSG/CD147 was prognostic of survival. This study provides the first description of the PSCC surfaceome and its relation to HPV infection and sets a foundation for novel biomarker and drug target discovery in this rare cancer.
13 Background: There are limited options for relapsed penile squamous cell carcinoma (PSCC) patients after definitive therapy or chemo-refractory disease. Novel target discovery methods are needed to identify potential treatment options and the cell surface represents an actionable target for molecular and cell-based therapies. We evaluated the cell surface molecular catalogue (e.g., surfaceome) in PSCC to identify underexplored targets. Methods: To evaluate proteins enriched on the surface of PSCC cells, we screened published translatomics data from 5 PSCC cell lines (HPV-negative). Ribosome-bound RNA expression values were then analyzed using a validated surfaceome gene list (n=2,886 proteins) to infer surface presence, which were grouped by consensus protein classes. This was complemented by RNA-Seq (n=37) on resected PSCC tumors (HPV+=16, HPV- = 16, unknown HPV status = 5). We used immunohistochemistry (IHC) to assess protein expression and subcellular localization in PSCC tumors; stain intensity was assessed by a semi-quantitative H-score. Non-parametric statistics compared distributions and Kaplan-Meier analysis estimated overall survival (OS; defined from surgery to death or last follow-up) and groups were compared by log-rank testing. The open-source DRPPM-PATH-SURVEIOR app and R statistical software were used to perform analyses. Results: We identified 604 unique surfaceome proteins which were represented in the top 75% of expression in the PSCC cell line translatome. Half of these proteins have N-glycosylations and 49.5% classified as high-confidence surface targets. The largest proportions of surfaceome proteins included: Receptors (25.6%), Transporters (18.5%), and proteins with unclassified function (32.2%). Of note, 16.2% of this surfaceome linked to at least one compound in the DrugBank database.There was a moderate correlation between cell line and tumor surfaceome RNAs (top 75%; r =0.58, p < 2.2x10-16). We selected targets in the 99% (BSG; CD147; regulates MMPs and lactate transport), 90% (FGFR1; receptor tyrosine kinase) and 75% (SLC16A1; metabolite transporter) of the surfaceome expression. Tumor RNA levels for BSG, FGFR1 and SLC16A1 were elevated, but without differences based on HPV. IHC demonstrated robust expression in tumors with plasma membrane scoring being enriched compared to non-plasma membrane compartments (CD147, p =2.9x10-6; SLC16A1, p = 5.1x10-6; FGFR1, p = 0.007). Of note, patients with elevated BSG RNA (based on median log2 value) had worse OS (p = 0.018), though this lost significance after adjusting for HPV. No differences in OS were seen with FGFR1 or SLC16A1 expression. Conclusions: Our analysis of the surfaceome based on RNA expression was associated with increased protein levels in tumor tissues. Evaluation of the PSCC surfaceome may provide opportunity to investigate novel therapeutic targets, which may be actionable regardless of HPV status.
Patients with squamous cell lung cancer (SCC) have high unmet medical need. Knowledge of these tumors is limited, and a lack of targetable genomic drivers means patients have few treatment options. To provide a detailed analysis on the influence of genomic alterations to proteome-level changes in SCC, we previously integrated DNA copy number, somatic mutations, RNA-sequencing, and expression proteomics in a cohort of 108 SCC patients. A major finding was identification of three proteomic subtypes, two of which made up the majority (87%) of tumors: the “Inflamed” subtype was enriched for B-cell rich tertiary lymphoid structures (TLS), and the “Redox” subtype was enriched for redox pathways and NFE2L2/KEAP1 alterations but had significantly less immune infiltration. We hypothesized these proteomic subtypes would give rise to distinct metabolic signatures. Therefore, we performed untargeted metabolomics on 87 tumors from the same cohort using chromatographic separation on a HILIC column, followed by analysis on a Q Exactive HF mass spectrometer. This analysis yielded 7,344 features corresponding to 7,072 unannotated metabolites and 272 identified metabolites. Glutathione, a key redox metabolite, was anticorrelated with immune score (R = -0.44, padj = 0.004) calculated from our transcriptomic data with the ESTIMATE algorithm, and glutathione was elevated in the Redox proteomic subtype (0.58 log2 ratio, padj = 9.87E-04). Consensus clustering was next used to identify novel metabolomic subtypes of SCC. Surprisingly, none of the five metabolomic subtypes we identified corresponded to proteomic subtype or NFE2L2/KEAP1 alteration (Fisher’s Exact test p-values > 0.05). The fifth subtype had 332 metabolites (26 identified) differentially expressed (> 1.5 fold-change, padj < 0.05) with ascorbate and aldarate metabolism as the top enriched pathway (padj = 3.36E-04). Interestingly, this fifth metabolomic subtype had significantly higher DNp63-alpha (p = 2.40E-05), a primary transcript of delta-N p63 that is known to promote non-small cell lung cancer. Ongoing integrative analyses across omic types will determine how p53, p63, and p73 transcripts influence these metabolomic subtypes, how these transcripts relate to the poor immune infiltration in some SCC tumors, and if these transcripts relate to novel metabolic vulnerabilities in SCC. Citation Format: Paul Stewart, Ashley Lui, Eric Welsh, Dalia Ercan, Vanessa Rubio, Hayley Ackerman, Guohui Li, Bin Fang, Steven Eschrich, John Koomen, Elsa Flores, Eric Haura, Gina DeNicola. Multi-omic landscape of squamous cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6029.
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