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Background In 2020, pembrolizumab was approved as a therapy for triple-negative breast cancer (TNBC) with the companion diagnostic DAKO 22C3 programmed death ligand-1 (PD-L1) immunohistochemistry assay. The study aimed to determine the landscape of PD-L1 expression as detected by the DAKO 22C3 PD-L1 assay in breast cancer subtypes and compare the clinicopathologic and genomic characteristics of PD-L1 positive and negative TNBC. Methods PD-L1 expression using the DAKO 22C3 antibody was scored using a combined positive score (CPS) and positive status was defined as CPS ≥10. Comprehensive genomic profiling was performed using the FoundationOne CDx assay. Results Of the 396 BC patients stained with DAKO 22C3, the majority were HR+/HER2− and TNBC (42% and 36%, respectively). Median PD-L1 expression and frequency of CPS ≥10 was highest in TNBC cases (median: 7.5, 50% CPS ≥10) and lowest in the HR+/HER2− group (median: 1.0, 15.5% CPS ≥10) (P Conclusions The subtypes of breast cancer have distinct patterns of PD-L1 expression, supporting that further research of immunotherapies may include specific evaluation of optimum cutoffs for non-TNBC patients. In TNBC, PD-L1 positivity is not associated with other clinicopathologic or genomic features and should be integrated into future studies of immunotherapy efficacy.

Background In patients with non-small cell lung cancer (NSCLC), 10%-40% will eventually develop brain metastases. We present the clinicopathologic, genomic, and biomarker landscape of a large cohort of NSCLC brain metastases (NSCLC-BM) samples. Materials and Methods We retrospectively analyzed 3035 NSCLC-BM tested with comprehensive genomic profiling (CGP) during routine clinical care. In addition, we compared the NSCLC-BM to a separate cohort of 7277 primary NSCLC (pNSCLC) specimens. Finally, we present data on 67 paired patients with NSCLC-BM and pNSCLC. Results Comprehensive genomic profiling analysis of the 3035 NSCLC-BMs found that the most frequent genomic alterations (GAs) were in the TP53, KRAS, CDKN2A, STK11, CDKN2B, EGFR, NKX2-1, RB1, MYC, and KEAP1 genes. In the NSCLC-BM cohort, there were significantly higher rates of several targetable GAs compared with pNSCLC, including ALK fusions, KRAS G12C mutations, and MET amplifications; and decreased frequency of MET exon14 skipping mutations (all P < .05). In the subset of NSCLC-BM (n = 1063) where concurrent PD-L1 immunohistochemistry (IHC) was performed, 54.7% of the patients with NSCLC-BM were eligible for pembrolizumab based on PD-L1 IHC (TPS ≥ 1), and 56.9% were eligible for pembrolizumab based on TMB-High status. In addition, in a series 67 paired pNSCLC and NSCLC-BM samples, 85.1% (57/67) had at least one additional GA discovered in the NSCLC-BM sample when compared with the pNSCLC sample. Conclusions Herein, we defined the clinicopathologic, genomic, and biomarker landscape of a large cohort of patients with NSCLC-BM which can help inform study design of future clinical studies for patients with NSCLC with BM. In certain clinical situations, metastatic NSCLC brain tissue or cerebral spinal fluid specimens may be needed to fully optimize personalized treatment.

Background In the current study, we examined the real-world prevalence of highly pigmented advanced melanomas (HPMel) and the clinicopathologic, genomic, and ICPI biomarker signatures of this class of tumors. Materials and Methods Our case archive of clinical melanoma samples for which the ordering physician requested testing for both PD-L1 immunohistochemistry (IHC) and comprehensive genomic profiling (CGP) was screened for HPMel cases, as well as for non-pigmented or lightly pigmented advanced melanoma cases (LPMel). Results Of the 1268 consecutive melanoma biopsies in our archive that had been submitted for PD-L1 IHC, 13.0% (165/1268) were HPMel and 87.0% (1103/1268) were LPMel. In the HPMel cohort, we saw a significantly lower tumor mutational burden (TMB, median 8.8 mutations/Mb) than in the LPMel group (11.4 mut/Mb), although there was substantial overlap. In examining characteristic secondary genomic alterations (GA), we found that the frequencies of GA in TERTp, CDKN2A, TP53, and PTEN were significantly lower in the HPMel cases than in LPMel. A higher rate of GA in CTNNB1, APC, PRKAR1A, and KIT was identified in the HPMel cohort compared with LPMel. Conclusions In this study, we quantified the failure rates of melanoma samples for PD-L1 testing due to high melanin pigmentation and showed that CGP can be used in these patients to identify biomarkers that can guide treatment decisions for HPMel patients. Using this practical clinical definition for tumor pigmentation, our results indicate that HPMel are frequent at 13% of melanoma samples, and in general appear molecularly less developed, with a lower TMB and less frequent secondary GA of melanoma progression.

OncoKids(SM) is a DNA and RNA-based Ampliseq panel designed at CHLA for clinical evaluation of pediatric hematologic malignancies and solid tumors. The DNA assay is designed to detect mutations in the full coding regions of 44 cancer loci; hotspot mutations in 82 genes; and amplification of 24 genes. The RNA content includes 70 driver genes and 1400 targeted gene fusions. Minimal input of 20ng DNA and RNA from frozen tissue or FFPE is required. To date we have prospectively evaluated 45 CNS tumor samples using OncoKids(SM). Twenty-six of 45 tumors (57%) had at least one variant of strong clinical significance (Tier I). For 33 of the 45 cases (73%) we also performed copy number DNA-based chromosomal microarray (CMA). Results were consistent between the two platforms in 13 of 33 (39%) cases. CMA demonstrated increased clinical utility in 11 (55%) of the remaining cases, while OncoKids(SM) provided more clinically useful information in 9 of 20 (45%) cases. For low-grade gliomas, BRAF V600E mutations or KIAA1549-BRAF fusions were detected by both platforms, whereas for high- grade gliomas OncoKids(SM) demonstrated diagnostic and prognostic HIST1H3B, FGFR1, ACVR1, and TP53 Tier I mutations. OncoKids(SM) analysis also revealed potential germline mutations in cancer predisposition genes. In contrast, CMA had greater utility for embryonal tumors, e.g. medulloblastomas with chromosomal gains and losses consistent with Group 3/4 tumors that were non-informative by OncoKids(SM). Our results demonstrate the clinical utility of CMA and OncoKids(SM) analyses for integrated reporting with pathology which have minimal sample requirements and rapid turnaround time.