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Background Immune checkpoint inhibitors such as pembrolizumab and nivolumab have emerged as active treatment options for patients with many cancers, including metastatic melanoma, but can also cause symptomatic or life‐threatening immune‐related adverse events, including encephalitis. Epididymitis and orchitis are rare complications of these therapies. Case Presentation We describe herein a patient with metastatic melanoma who developed epididymo‐orchitis followed by encephalitis while receiving pembrolizumab. The patient developed testicular pain and fever after his third dose of pembrolizumab; ultrasound evaluation demonstrated bilateral epididymo‐orchitis. He then developed headaches, fever, and altered mental status over the next week and was admitted to the hospital. Lumbar puncture revealed inflammatory changes consistent with meningoencephalitis; he did not improve with broad‐spectrum antibiotics, and an extensive workup for infectious etiologies, including cerebrospinal fluid testing using a clinical metagenomic next‐generation sequencing assay, was negative. He received high‐dose steroids for suspected autoimmune encephalitis, and both his orchitis and meningoencephalitis improved rapidly after one dose. He fully recovered after a 5‐week taper of oral steroids. Discussion Here, we report a case of epididymo‐orchitis complicating immune checkpoint inhibitor therapy. This patient subsequently developed severe encephalitis but rapidly improved with steroids. Clinicians should be aware of rare complications of these agents. Key Points Epididymo‐orchitis is a rare and potentially life‐threatening complication of anti‐programmed death protein 1 (anti‐PD‐1) therapy. For patients on anti‐PD‐1 therapy who develop either epididymo‐orchitis or epididymitis without clear infectious cause, immune‐related adverse events should be considered in the differential diagnosis. If severe, epididymo‐orchitis related to anti‐PD‐1 therapy may be treated with high‐dose corticosteroids.

Genomic technologies including microarrays and next-generation sequencing have enabled the generation of molecular signatures of prostate cancer. Lists of differentially expressed genes between malignant and non-malignant states are thought to be fertile sources of putative prostate cancer biomarkers. However such lists of differentially expressed genes can be highly variable for multiple reasons. As such, looking at differential expression in the context of gene sets and pathways has been more robust. Using next-generation genome sequencing data from The Cancer Genome Atlas, differential gene expression between age- and stage- matched human prostate tumors and non-malignant samples was assessed and used to craft a pathway signature of prostate cancer. Up- and down-regulated genes were assigned to pathways composed of curated groups of related genes from multiple databases. The significance of these pathways was then evaluated according to the number of differentially expressed genes found in the pathway and their position within the pathway using Gene Set Enrichment Analysis and Signaling Pathway Impact Analysis. The “transforming growth factor-beta signaling” and “Ran regulation of mitotic spindle formation” pathways were strongly associated with prostate cancer. Several other significant pathways confirm reported findings from microarray data that suggest actin cytoskeleton regulation, cell cycle, mitogen-activated protein kinase signaling, and calcium signaling are also altered in prostate cancer. Thus we have demonstrated feasibility of pathway analysis and identified an underexplored area (Ran) for investigation in prostate cancer pathogenesis.

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability in response to targeted therapies is well known. The existence of additional genomic alterations among tumor cells can only partially explain this variability. As such, nongenetic factors are increasingly seen as critical contributors to tumor relapse and acquired resistance in cancer. Here, we show that both genetic and nongenetic factors contribute to targeted drug response variability in an experimental model of tumor heterogeneity. We observe significant variability to epidermal growth factor receptor (EGFR) inhibition among and within multiple versions and clonal sublines of PC9, a commonly used EGFR mutant nonsmall cell lung cancer (NSCLC) cell line. We resolve genetic, epigenetic, and stochastic components of this variability using a theoretical framework in which distinct genetic states give rise to multiple epigenetic “basins of attraction,” across which cells can transition driven by stochastic noise. Using mutational impact analysis, single-cell differential gene expression, and correlations among Gene Ontology (GO) terms to connect genomics to transcriptomics, we establish a baseline for genetic differences driving drug response variability among PC9 cell line versions. Applying the same approach to clonal sublines, we conclude that drug response variability in all but one of the sublines is due to epigenetic differences; in the other, it is due to genetic alterations. Finally, using a clonal drug response assay together with stochastic simulations, we attribute subclonal drug response variability within sublines to stochastic cell fate decisions and confirm that one subline likely contains genetic resistance mutations that emerged in the absence of drug treatment.

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability of targeted therapy response is observed. Additional genetic mutations can only partially explain this variability, leading to consideration of non-genetic factors, such as "stem-like" and "mesenchymal" phenotypic states, as critical contributors to tumor relapse and resistance. Here, we show that both genetic and non-genetic factors contribute to targeted drug-response variability in an experimental tumor heterogeneity model based on multiple versions and clonal sublines of PC9, the archetypal EGFR-mutant non-small cell lung cancer cell line. We observe significant drugresponse variability across PC9 cell line versions, among sublines, and within sublines. To disentangle genetic, epigenetic, and stochastic components underlying this variability, we adopt a theoretical framework whereby distinct genetic states give rise to multiple epigenetic "basins of attraction", across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Using mutational impact analysis, single-cell differential gene expression, and semantic similarity of gene ontology terms to connect genomics and transcriptomics, we establish a baseline of genetic differences explaining drug-response variability across PC9 cell line versions. In contrast, with the same approach, we conclude that in all but one of the clonal sublines, drug-response variability is due to epigenetic rather than genetic differences. Finally, using a clonal drug-response assay and stochastic simulations, we attribute drug-response variability within sublines to intracellular stochastic fluctuations and confirm that one subline likely contains a genetic resistance mutation that emerged in the absence of selective pressures. We propose that a theoretical framework deconvolving the complex interplay among genetic, epigenetic, and stochastic sources of intratumoral heterogeneity will lead to novel therapeutic strategies to combat tumor relapse and resistance.A theoretical framework for understanding the connections between genetic and non-genetic sources of tumor heterogeneity is the "epigenetic landscape," which was proposed by Waddington over 50 years ago 34 but has received renewed attention recently 16,17,35,36 . In analogy to the potential energy landscape of physical chemistry, Waddington posited that a cellular state can be assigned a "quasi-potential" energy and placed within a landscape where local minima correspond to cellular phenotypes. Phenotypic state transitions occur when cells traverse the barriers separating adjacent basins, driven by intrinsic or extrinsic sources of noise 37,38 . Importantly, the topography of the epigenetic landscape depends on a complex set of biochemical interactions within (and possibly spanning 39 ) cells and the values of associated rate parameters 40,41 . Many of these parameters depend strongly on protein stru...

◥Melanomas harboring BRAF mutations can be treated with BRAF inhibitors (BRAFi), but responses are varied and tumor recurrence is inevitable. Here we used an integrative approach of experimentation and mathematical flux balance analyses in BRAFmutated melanoma cells to discover that elevated antioxidant capacity is linked to BRAFi sensitivity in melanoma cells. High levels of antioxidant metabolites in cells with reduced BRAFi sensitivity confirmed this conclusion. By extending our analyses to other melanoma subtypes in The Cancer Genome Atlas, we predict that elevated redox capacity is a general feature of mela-nomas, not previously observed. We propose that redox vulnerabilities could be exploited for therapeutic benefits and identify unsuspected combination targets to enhance the effects of BRAFi in any melanoma, regardless of mutational status.Significance: An integrative bioinformatics, flux balance analysis, and experimental approach identify targetable redox vulnerabilities and show the potential for modulation of cancer antioxidant defense to augment the benefits of existing therapies in melanoma.

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