Klebig, Mitchell

Abstract Background: Pembrolizumab has been increasingly used off label for recurrent gliomas, yet biomarkers predicting response are poorly defined. Gliomas exhibit substantial molecular heterogeneity across Glioblastoma, IDH-wildtype (GBM), Astrocytoma, IDH-Mutant (A-IDHm), and Oligodendroglioma, 1p/19q co-deleted (OLIGO), which may influence immunotherapy efficacy. This study aimed to identify molecular predictors of progression-free survival (PFS) in recurrent glioma patients treated with pembrolizumab. Methods: Adults ≥18 years with recurrent glioma receiving ≥2 cycles of pembrolizumab between 2014 - 2024 were retrospectively identified across Mayo Clinic. Next-generation sequencing (NGS) reports were reviewed and archival tumor tissue resected prior to pembrolizumab initiation was analyzed when available. Comprehensive molecular profiling was performed using the Mayo Clinic Solid Tumor Panel which employs the Illumina Tru-Sight Oncology 500 High-Throughput NGS assay. Progression was assessed using RANO 2.0 criteria. Genomic alterations (clinically relevant sequences and/or copy-number variants) were evaluated using the Kaplan-Meier method, with differences in PFS compared using the log-rank test. Results: Thirty-three patients were included [median (range) age: 44.0 (21-76) years; 63.6% male]. The interval between tumor tissue sampling and pembrolizumab initiation was 9.9 (0.9-176.1) months, and median treatment duration was 2.8 (1.4-10.4) months. Median PFS for the overall cohort was 2.4 (0.8-15.2) months, and median overall survival from pembrolizumab initiation was 6.9 (0.9-48.2) months. Patients with OLIGO (n=8) had a longer PFS [4.6 (1.9-15.2) months] than either A-IDHm [n=11; PFS 2.1 (1.1-4.4) months] or GBM [n=14; PFS 2.3 (0.8-9.2) months]. Within OLIGO, CDKN2A/B heterozygous deletion (n=3) predicted a shorter PFS (3.9 vs 10.9 months; p=0.0462), while in A-IDHm, FANC mutation (n=2) was associated with a longer PFS (4.17 vs 1.61 months; p=0.0224). No significant associations with PFS were observed for other altered genes or pathways evaluated, including but not limited to Tumor Mutational Burden, EGFR, RB1, TP53, FUBP1, NF 1 or 2, PTEN, PDGFRA, PIK3CA, PIK3R1, CDK4, KRAS, MLH1, MLH2, MSH6 genomic alterations or CDKN2A/B homozygous deletion (all p>0.05). Conclusions: Pembrolizumab shows limited overall efficacy in recurrent gliomas, however, exploratory analyses identified several subtype-specific genomic alterations that may correlate with PFS. These hypothesis-generating findings highlight the potential influence of underlying tumor biology on immunotherapy response and warrant further validation in larger, prospective cohorts. Citation Format: Shameel Shafqat, Muhammad Asad Maqbool, Hussam Al Kateb, Terry C. Burns, Jian L. Campian, Shannon P. Fortin Ensign, Evanthia Galanis, Julie E. Hammack, Cristaine M. Ida, Mitch L. Klebig, Timothy J. Kaufmann, Autumn C. Moon, Maciej M. Mrugala, Bryan J. Neth, Alyx B. aPorter, Michael W. Ruff, Ugur T. Sener, Wendy J. Sherman, Joon H. Uhm, Rachael A. Vaubel, Sani H. Kizilbash. Molecular correlates of progression-free survival in recurrent gliomas treated with pembrolizumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 5253.

Abstract Introduction Accurate detection of gene fusions is critical for the diagnosis and management of sarcomas. However, occasional false-negative results may occur due to factors such as low tumor cellularity, limited assay coverage of relevant genomic regions, or mis-annotation by bioinformatic pipelines. We recently encountered a case in which our clinical SARCP fusion detection assay failed to identify an HMGA2::NCOR2 (exon 3–exon 16) fusion. Method The SARCP assay is a targeted, amplicon-based RNA-seq next-generation sequencing (NGS) assay designed to detect gene fusions across 138 genes, including HMGA2. Although NCOR2 is not among the targeted genes, the assay is capable of detecting fusions when only one gene partner is represented. Results Suspicion of a false-negative result arose when the pathologist noted that the tumor’s histologic features—keratin-positive, giant cell-rich soft tissue—were consistent with a subtype previously associated with the HMGA2::NCOR2 fusion. This prompted a review of the bioinformatic output, which had erroneously reported an HMGA2::MAML2 fusion. The misannotation was traced to sequence homology involving a CAA/CAG repeat at the 5′ end of NCOR2 exon 16, likely resulting from DNA polymerase slippage and misalignment in low-complexity, partially complementary repetitive regions. This erroneously lead to the target genomic sequence getting mapped to MAML2 exon 2 as opposed to the NCOR2 exon 16. Discussion This case highlights how bioinformatic mis-annotation can lead to occasional false-negative fusion calls. It underscores the importance of manual review in cases with strong clinical or pathologic suspicion and calls attention to the need for fusion-calling algorithms that better handle repetitive and homopolymeric sequences. Citation Format: Ganesh P. Pujari, Mitch L. Klebig, Kurt S. Willkom, Montha Chhunn, Stefan W. Nelson, Neiladri Saha, Kevin C. Halling. Mis-Annotation of an HMGA2::NCOR2 Fusion in FFPE Sarcoma Samples: A Case Illustrating Bioinformatic Limitations in Fusion Detection [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Fusion-Positive Cancer: From Discovery to Therapy; 2026 Jan 13-15; Philadelphia PA. Philadelphia (PA): AACR; Cancer Res 2026;86(1_Suppl):Abstract nr A012.

Abstract Synthetic lethal interactions enable a novel approach for discovering specific genetic vulnerabilities in cancer cells that can be exploited for the development of therapeutics. This concept has recently been exploited in the development of PARP inhibitors as novel chemotherapeutics for breast cancer. While PARP is not essential in normal cells, BRCA mutant cells are dependent on it for their survival. This led to the successful treatment of BRCA mutant tumors of the breast, ovary, and prostate with the oral PARP inhibitor, olaparib. Therapeutic strategies based on such synthetic-lethal (SL) interactions can enable drug targeting of cancer-specific alterations for otherwise undruggable tumor suppressors. Large-scale analyses of genetic interaction networks in model organisms like yeast suggest that disease-specific networks should not only give rise to destructive phenotypes (e.g. uncontrolled cell growth), but will also present unique vulnerabilities that can be exploited for novel therapies. Despite successes in model organisms such as yeast, discovering synthetic lethal interactions on a large scale in human cells remains a significant challenge. We have used a combination of computational and experimental approach whereby yeast interactions between human orthologs are filtered by cancer association and prioritized by genomic features, and candidates from the prioritized list are then validated in human cell lines using an RNA interference approach. As a proof of principle, we utilized this approach to discover two previously unknown synthetic lethal/sick interactions, one between SMARCB1 (yeast SNF5) and PSMA4 (yeast PRE9), and another between ASPSCR1 (yeast UBX4) and PSMC2 (yeast RPT1) based on shRNA double knock-down in normal human fibroblast cells. These interactions suggest potentially new therapeutic targets for SMARCB1 and ASPSCR1 mutated cancers, and more broadly, illustrate the potential of this cross-species approach. Citation Format: Michael K. Asiedu, Raamesh Deshpande, Mitchell Klebig, Shari Sutor, Elena Kuzmin, Jeff Piotrowski, Seung Ho Shin, Michael Costanzo, Charles Boone, Dennis A. Wigle, Chad L Myers. A comparative genomic approach for identifying synthetic lethal interactions in human cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-234. doi:10.1158/1538-7445.AM2013-LB-234

Abstract Synthetic lethal interactions enable a novel approach for discovering specific genetic vulnerabilities in cancer cells that can be exploited for the development of therapeutics. Despite successes in model organisms such as yeast, discovering synthetic lethal interactions on a large scale in human cells remains a significant challenge. We describe a comparative genomic strategy for identifying cancer-relevant synthetic lethal interactions whereby candidate interactions are prioritized on the basis of genetic interaction data available in yeast, followed by targeted testing of candidate interactions in human cell lines. As a proof of principle, we describe two novel synthetic lethal interactions in human cells discovered by this approach, one between the tumor suppressor gene SMARCB1 and PSMA4, and another between alveolar soft-part sarcoma-associated ASPSCR1 and PSMC2. These results suggest therapeutic targets for cancers harboring mutations in SMARCB1 or ASPSCR1 and highlight the potential of a targeted, cross-species strategy for identifying synthetic lethal interactions relevant to human cancer. Cancer Res; 73(20); 6128–36. ©2013 AACR.