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Immune-checkpoint inhibitors (ICI) have revolutionized the therapeutic landscape of cancer. However, optimal patient selection is still an unmet need. One-hundred-forty-six patients with metastatic cancer candidates to ICI at the Hospital Clinic of Barcelona Clinical Trials Unit were prospectively recruited in this observational study. Blood samples were collected at different timepoints, baseline LIPI score calculated and pre-ICI archived tissues retrieved to evaluate PD-L1, tumor-infiltrating lymphocytes (TILs) and PD1 mRNA levels. Tumor assessments were centrally reviewed by RECIST 1.1 criteria. Associations with overall response rates (ORR), durable clinical benefit (DCB), progression-free survival (PFS) and overall survival (OS) were performed with univariable/multivariable logistic and Cox regressions, where appropriate. At a median follow-up of 26.9 months, median PFS and OS were 2.7 and 12.9 months. Response rates were 17.8% with duration of response (DOR) of 4.4 months. LIPI score was independently associated with PFS (p = 0.025) and OS (p p = 0.005). Time-to-best response (TTBR) and ORR (p p p = 0.028) and DCB (univariate p = 0.043). PD1 mRNA levels were strikingly associated to complete responses (p = 0.021). To resume, in our prospective observational pan-cancer study, baseline LIPI score, immunotherapy-naïve status, cancer type and RT before starting ICI were the most relevant clinical factors independently correlated with immunotherapy outcomes. Longer TTBR seemed to associate with better survival, while PD1 mRNA and PD-L1 protein levels might be tumor-agnostic predictive factors of response to ICI and should be furtherly explored.

Dataset of 65 tumor samples.

Expression of the 23 genes and signatures across the 3 cancer groups in the nCounter-based dataset

Antibody targeting of the immune checkpoint receptor PD1 produces therapeutic activity in a variety of solid tumors, but most patients exhibit partial or complete resistance to treatment for reasons that are unclear. In this study, we evaluated tumor specimens from 65 patients with melanoma, lung nonsquamous, squamous cell lung or head and neck cancers who were treated with the approved PD1-targeting antibodies pembrolizumab or nivolumab. Tumor RNA before anti-PD1 therapy was analyzed on the nCounter system using the PanCancer 730-Immune Panel, and we identified 23 immune-related genes or signatures linked to response and progression-free survival (PFS). In addition, we evaluated intra- and interbiopsy variability of PD1, PD-L1, CD8A, and CD4 mRNAs and their relationship with tumor-infiltrating lymphocytes (TIL) and PD-L1 IHC expression. Among the biomarkers examined, PD1 gene expression along with 12 signatures tracking CD8 and CD4 T-cell activation, natural killer cells, and IFN activation associated significantly with nonprogressive disease and PFS. These associations were independent of sample timing, drug used, or cancer type. TIL correlated moderately (∼0.50) with PD1 and CD8A mRNA levels and weakly (∼0.35) with CD4 and PD-L1. IHC expression of PD-L1 correlated strongly with PD-L1 (0.90), moderately with CD4 and CD8A, and weakly with PD1. Reproducibility of gene expression in intra- and interbiopsy specimens was very high (total SD Cancer Res; 77(13); 3540–50. ©2017 AACR.

4152 Background: Despite huge efforts patients (pts) with advanced PDAC, still have a dismal long-term prognosis. The lack of available good-quality tissue samples for next generation sequencing (NGS) prevents from finding actionable alterations that could guide personalized treatments. Circulating tumor DNA (ctDNA) provides a non-invasive method for obtaining molecular information with therapeutic potential. Here, we present prospective data of ctDNA sequencing in pts with PDAC. Methods: We collected a single blood sample from advanced PDAC pts at any line of treatment (Tx) and at least 10 days apart from their last therapy. The samples were analyzed by Guardant360 plasma-based NGS, a standardized assay which covers microsatellite instability [MSI] evaluation and analysis of all four types of somatic alterations in 74 genes. Alterations were reported either as pathogenic or non-pathogenic. We classified each gene alteration according to the different OncoKB therapeutic levels of evidence [LE]. Additionally, we gathered the dates of both blood collection and molecular report. In case the molecular report showed no tumor-related alterations, it was interpreted as either absence of detectable mutations or low ctDNA levels, which would translate low disease burden or pts responding to therapy. Demographic and clinical data have been accessed from the medical records. Results: From 08/2019 to 09/2021 we collected blood samples from 94 PDAC pts. 56% of them were male and 53% were >65 years old. At the time of sample collection, nearly all pts were metastatic (98%). Regarding previous lines of Tx, 57% pts were Tx naïve; 10% were receiving active systemic Tx and 33% had experienced disease progression. Molecular reports were available in an average of 9.1 days. A total of 243 gene alterations were detected, having 94% of pts at least 1 genomic alteration, which was pathogenic in 69% of the cases (see Table). There were no pathogenic alterations ranked as OncoKB LE 1-2 ( MSI or NTRK). Seventy alterations (30%) were ranked as OncoKB LE 3A and 4 ( ARID1A, BRAC2, CDKN2A, KRAS). Three of these pts were treated with PARP inhibitors due to the presence of BRCA2 mutations. No ctDNA was detected in 15 pts (16%), despite being the sample collected >10 days from receiving their last Tx. Of these, 11 had low tumor burden (only peritoneal or lung metastases) and 4 had documented response to the Tx by the time the samples were collected. Conclusions: Real-time and prospective genomic profiling of pts with advanced PDAC using ctDNA is feasible and conveniently fast, which would allow its role in identifying and developing therapeutic targets for approved Tx or clinical trial treatments. [Table: see text]