BACKGROUND: Metastases are the hallmark of lethal cancer, though underlying mechanisms that drive metastatic spread to specific organs remain poorly understood. Renal cell carcinoma (RCC) is known to have distinct sites of metastases, with lung, bone, liver, and lymph nodes being more common than brain, gastrointestinal tract, and endocrine glands. Previous studies have shown varying clinical behavior and prognosis associated with the site of metastatic spread; however, little is known about the molecular underpinnings that contribute to the differential outcomes observed by the site of metastasis. METHODS: We analyzed primary renal tumors and tumors derived from metastatic sites to comprehensively characterize genomic and transcriptomic features of tumor cells as well as to evaluate the tumor microenvironment at both sites. RESULTS: We included a total of 657 tumor samples (340 from the primary site [kidney] and 317 from various sites of metastasis). We show distinct genomic alterations, transcriptomic signatures, and immune and stromal tumor microenvironments across metastatic sites in a large cohort of patients with RCC. CONCLUSION: We demonstrate significant heterogeneity among primary tumors and metastatic sites and elucidate the complex interplay between tumor cells and the extrinsic tumor microenvironment that is vital for developing effective anticancer therapies.

Recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) patients overall have a poor prognosis. However, human papillomavirus (HPV)-associated R/M oropharyngeal squamous cell carcinoma (OPSCC) is associated with a better prognosis compared to HPV−negative disease. Immune checkpoint blockade (ICB) is the standard of care for R/M HNSCC. However, whether HPV and its surrogate marker, p16, portend an improved response to ICB remains controversial. We queried the Caris Life Sciences CODEai database for p16+ and p16− HNSCC patients using p16 as a surrogate for HPV. A total of 2905 HNSCC (OPSCC, n = 948) cases were identified. Of those tested for both HPV directly and p16, 32% (251/791) were p16+ and 28% (91/326) were HPV+. The most common mutation in the OPSCC cohort was TP53 (33%), followed by PIK3CA (17%) and KMT2D (10.6%). TP53 mutations were more common in p16− (49%) versus the p16+ group (10%, p < 0.0005). Real-world overall survival (rwOS) was longer in p16+ compared to p16− OPSCC patients, 33.3 vs. 19.1 months (HR = 0.597, p = 0.001), as well as non-oropharyngeal (non-OP) HNSCC patients (34 vs. 17 months, HR 0.551, p = 0.0001). There was no difference in the time on treatment (TOT) (4.2 vs. 2.8 months, HR 0.796, p = 0.221) in ICB-treated p16+ vs. p16− OPSCC groups. However, p16+ non-OP HNSCC patients treated with ICB had higher TOT compared to the p16− group (4.3 vs. 3.3 months, HR 0.632, p = 0.016), suggesting that p16 may be used as a prognostic biomarker in non-OP HNSCC, and further investigation through prospective clinical trials is warranted.

Purpose: Oncogenic mutations in KRAS have been identified in >85% of pancreatic ductal adenocarcinoma (PDAC) cases, with G12D, G12V, and G12R being the most frequent variants. Using large clinical and genomic databases, this study characterizes prognostic and molecular differences between KRAS variants, focusing on KRASG12D and KRASG12R. Experimental Design: PDAC samples were tested using DNA and RNA sequencing. The MAPK activation score and tumor microenvironment were analyzed from RNA expression data. Real-world overall survival (OS) obtained from insurance claims data was calculated from tissue collection to last contact. Significance was determined by χ2 and Fisher exact tests. Results: A total of 3,755 patients with PDAC harboring KRASG12D (n = 1,766), KRASG12V (n = 1,294), KRASG12R (n = 621), or KRASG12C (n = 74) variants were identified. Patients with G12R mutations had longer OS compared with those with G12D overall (12.7 vs. 10.1 months; P value = 0.0001), with similar trends in patients treated with gemcitabine/nab-paclitaxel (13.5 vs. 10.4 months; P value = 0.0002) or FOLFIRINOX (18.3 vs. 14.0 months; P value<0.001). ARID1A and KMT2D mutations were more frequent in the G12D subgroup. Several genes involved in glucose and glutamine metabolism were less expressed in G12R compared with G12D. PD-L1 expression was lower in G12R compared with G12D (13% vs. 19%). Conclusions: KRAS G12D tumors exhibited a distinct molecular profile compared with G12R tumors, including genes involved in the MAPK pathway, immune activation, and glucose and glutamine metabolism. Patients with G12D mutations had lower OS compared with those with G12R. Based on these data, future studies should address the KRAS mutation status and explore distinct therapeutic vulnerabilities.

Melanoma brain metastases (MBM) are clinically challenging to treat and exhibit variable responses to immune checkpoint therapies. Prior research suggests that MBM exhibit poor tumor immune responses and are enriched in oxidative phosphorylation. Here, we report results from a multi-omic analysis of a large, real-world melanoma cohort. MBM exhibited lower interferon-gamma (IFNγ) scores and T cell-inflamed scores compared to primary cutaneous melanoma (PCM) or extracranial metastases (ECM), which was independent of tumor mutational burden. Among MBM, there were fewer computationally inferred immune cell infiltrates, which correlated with lower TNF and IL12B mRNA levels. Ingenuity pathway analysis (IPA) revealed suppression of inflammatory responses and dendritic cell maturation pathways. MBM also demonstrated a higher frequency of pathogenic PTEN mutations and angiogenic signaling. Oxidative phosphorylation (OXPHOS) was enriched in MBM and negatively correlated with NK cell and B cell-associated transcriptomic signatures. Modulating metabolic or angiogenic pathways in MBM may improve responses to immunotherapy in this difficult-to-treat patient subset.

Molecular profiling of clear cell renal cell carcinoma (ccRCC) tumors of patients in a clinical trial has identified distinct transcriptomic signatures with predictive value, yet data in non–clear cell variants (nccRCC) are lacking. We examined the transcriptional profiles of RCC tumors representing key molecular pathways, from a multi-institutional, real-world patient cohort, including ccRCC and centrally reviewed nccRCC samples. ccRCC had increased angiogenesis signature scores compared with the heterogeneous group of nccRCC tumors, while cell cycle, fatty acid oxidation/AMPK signaling, and fatty acid synthesis/pentose phosphate signature scores were increased in one or more nccRCC subtypes. Among both ccRCC and nccRCC tumors, T effector scores statistically correlated with increased immune cell infiltration and were more commonly associated with immunotherapy-related markers (PD-L1 ⁺ /TMB ^hi /MSI ^hi ). In conclusion, this study provides evidence of differential gene transcriptional profiles among ccRCC versus nccRCC tumors, providing insights for optimizing personalized and histology-specific therapeutic strategies for patients with advanced RCC.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease that is challenging to detect at an early stage. Biomarkers are needed that can detect PDAC early in the course of disease when interventions lead to the best outcomes. We highlight study design and statistical considerations that inform pancreatic cancer early detection biomarker evaluation. We describe experimental design strategies in this setting useful for streamlining biomarker evaluation at each Early Detection Research Network (EDRN) phase of biomarker development. We break the early EDRN phases into sub-phases, proposing objectives, study design strategies, and biomarker performance benchmarks. The goal of early detection in populations at high-risk of PDAC is described. Evaluating biomarker behavior in patients under surveillance without disease can winnow candidate biomarkers. Potential resources for biomarker validation studies are described. Multisite and multidisciplinary collaboration can facilitate study design strategies in this lethal but low incidence disease and streamline the path from biomarker discovery to clinical use. Improvements in analytical and experimental design methods could help accelerate biomarker evaluation through the phases of biomarker development.