Abstract: A third of humans carry genetic variants of the ITP pyrophosphatase (ITPase) gene ( ITPA ) that lead to reduced enzyme activity. Reduced ITPase activity was earlier reported to protect against ribavirin-induced hemolytic anemia and to diminish relapse following ribavirin and interferon therapy for hepatitis C virus (HCV) genotype 2 or 3 infections. While several hypotheses have been put forward to explain the antiviral actions of ribavirin, details regarding the mechanisms of interaction between reduced ITPase activity and ribavirin remain unclear. The in vitro effect of reduced ITPase activity was assessed by means of transfection of hepatocytes (Huh7.5 cells) with a small interfering RNA (siRNA) directed against ITPA or a negative-control siRNA in the presence or absence of ribavirin in an HCV culture system. Low ribavirin concentrations strikingly depleted intracellular GTP levels in HCV-infected hepatocytes whereas higher ribavirin concentrations induced G-to-A and C-to-U single nucleotide substitutions in the HCV genome, with an ensuing reduction of HCV RNA expression and HCV core antigen production. Ribavirin triphosphate (RTP) was dephosphorylated in vitro by recombinant ITPase to a similar extent as ITP, a naturally occurring substrate of ITPase, and reducing ITPA expression in Huh 7.5 cells by siRNA increased intracellular levels of RTP in addition to increasing HCV mutagenesis and reducing progeny virus production. Our results extend the understanding of the biological impact of reduced ITPase activity, demonstrate that RTP is a substrate of ITPase, and may point to personalized ribavirin dosage according to ITPA genotype in addition to novel antiviral strategies. IMPORTANCE This study highlights the multiple modes of action of ribavirin, including depletion of intracellular GTP and increased hepatitis C virus mutagenesis. In cell culture, reduced ITP pyrophosphatase (ITPase) enzyme activity affected the intracellular concentrations of ribavirin triphosphate (RTP) and augmented the impact of ribavirin on the mutation rate and virus production. Additionally, our results imply that RTP, similar to ITP, a naturally occurring substrate of ITPase, is dephosphorylated in vitro by ITPase.

Abstract: Background: Increased tumor mutational burden (TMB) and inflammation are associated with improved clinical outcomes to immuno-oncology (I-O) therapy in many tumor types. Genomic correlates of response to nivolumab (N) vs dacarbazine (D) (CheckMate [CM] 066; NCT01721772) and N+ipilimumab (I) combination therapy or N vs I (CM 067; NCT01844505) were evaluated for association of TMB and an inflammatory gene signature with clinical outcomes. Methods: In pretreatment tumor samples from eligible patients (pts), TMB was analyzed by whole-exome sequencing using median number of total missense mutations to define high vs low TMB (TMB-H/TMB-L). Associations of TMB with progression-free survival (PFS) and overall survival (OS) were evaluated per protocol-defined exploratory analyses using 4-year follow-up data for both trials. PFS and OS associations with an inflammatory signature were assessed by RNAseq in CM 067 samples only and grouped into tertiles for analysis. HR and 95% CI were calculated using Cox modeling and P values were calculated using the Wald test. Results: In CM 066, TMB was evaluable in 122 of 411 pts. PFS and OS were significantly longer in pts treated with N, but not with D, for TMB-H vs TMB-L tumors. The benefit of PFS and OS for N vs D was greater in pts with TMB-H than TMB-L (Table). In CM 067, 583 of 937 pts were evaluable for TMB and 299 were evaluable using an inflammatory signature. PFS and OS were longer in each treatment (tx) arm in pts with TMB-H vs TMB-L (Table). Across tx arms, a numerical benefit was observed for PFS and OS in pts with high vs low inflammatory signature (Table). TMB-H and a high inflammatory signature score were independently associated with clinical outcomes to I-O. Conclusions: High TMB or high inflammatory signature was associated with benefit to I-O. TMB status did not differentiate between N+I and N, and higher inflammatory status increased the likelihood of benefit for N+I and N, suggesting further evaluation of these biomarkers to characterize the response to I-O regimens in melanoma. Association of TMB (CM 066) or TMB and inflammatory signature (CM 067) with PFS and OSCategorical comparisonClinical measureHR (95% CI; P value)CM 066NDPatients with evaluable TMB, n (high, low)53 (23, 30)69 (38, 31)TMB-H vs TMB-LPFSOS0.33 (0.16-0.69; 0.0031)0.43 (0.2-0.91; 0.027)0.67 (0.39-1.10; 0.13)0.66 (0.39-1.10; 0.13)N vs D in TMB-HPFSOS0.28 (0.14-0.59; 0.00083)0.35 (0.17-0.73; 0.0046)N vs D in TMB-LPFSOS0.57 (0.33-0.99; 0.047)0.55 (0.31-0.98; 0.044)Categorical comparisonClinical measureHR (95% CI; P value)CM 067N+INIPatients with evaluable TMB, n (high, low)197 (94, 103)192 (95, 97)194 (101, 93)TMB-H vs TMB-LPFSOS0.56 (0.39-0.81; 0.002)0.53 (0.34-0.81; 0.0032)0.45 (0.31-0.65; 0.00002)0.48 (0.31-0.72; 0.00046)0.64 (0.47-0.87; 0.005)0.59 (0.42-0.83; 0.0022)N+I vs N in TMB-HPFSOS0.95 (0.63-1.40; 0.81)0.97 (0.60-1.60; 0.88)-N+I vs N in TMB-LPFSOS0.77 (0.56-1.10; 0.12)0.87 (0.61-1.30; 0.46)-Patients with evaluable inflammatory signature, n (low, med, high)93 (33, 32, 28)106 (39, 31, 36)100 (28, 36, 36)Inflammatory signature, high vs lowPFSOS0.38 (0.18-0.80; 0.01)0.53 (0.24-1.18; 0.12)0.60 (0.34-1.00; 0.069)0.35 (0.18-0.69; 0.0025)0.48 (0.27-0.85; 0.012)0.52 (0.27-1.00; 0.049) Citation Format: F. Stephen Hodi, Jedd D. Wolchok, Dirk Schadendorf, James Larkin, Max Qian, Abdel Saci, Tina C. Young, Sujaya Srinivasan, Han Chang, Megan Wind-Rotolo, Jasmine I. Rizzo, Donald G. Jackson, Paolo A. Ascierto. Genomic analyses and immunotherapy in advanced melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT037.

Abstract: Adjuvant immunotherapy produces durable benefit for patients with resected melanoma, but many develop recurrence and/or immune-related adverse events (irAE). We investigated whether baseline serum autoantibody (autoAb) signatures predicted recurrence and severe toxicity in patients treated with adjuvant nivolumab, ipilimumab, or ipilimumab plus nivolumab. Experimental Design: This study included 950 patients: 565 from CheckMate 238 (408 ipilimumab versus 157 nivolumab) and 385 from CheckMate 915 (190 nivolumab versus 195 ipilimumab plus nivolumab). Serum autoAbs were profiled using the HuProt Human Proteome Microarray v4.0 (CDI Laboratories, Mayaguez, PR). Analysis of baseline differentially expressed autoAbs was followed by recurrence and severe toxicity signature building for each regimen, testing of the signatures, and additional independent validation for nivolumab using patients from CheckMate 915. Results: In the nivolumab independent validation cohort, high recurrence score predicted significantly worse recurrence-free survival [RFS; adjusted HR (aHR), 3.60; 95% confidence interval (CI), 1.98–6.55], and outperformed a model composed of clinical variables including PD-L1 expression (P & lt; 0.001). Severe toxicity score was a significant predictor of severe irAEs (aHR, 13.53; 95% CI, 2.59–86.65). In the ipilimumab test cohort, high recurrence score was associated with significantly worse RFS (aHR, 3.21; 95% CI, 1.38–7.45) and severe toxicity score significantly predicted severe irAEs (aHR, 11.04; 95% CI, 3.84–37.25). In the ipilimumab plus nivolumab test cohort, high autoAb recurrence score was associated with significantly worse RFS (aHR, 6.45; 95% CI, 1.48–28.02), and high severe toxicity score was significantly associated with severe irAEs (aHR, 23.44; 95% CI, 4.10–212.50). Conclusions: Baseline serum autoAb signatures predicted recurrence and severe toxicity in patients treated with adjuvant immunotherapy. Prospective testing of the signatures that include datasets with longer follow-up and rare but more severe toxicities will help determine their generalizability and potential clinical utility. See related commentary by Hassel and Luke, p. 3914

Abstract: Although next-generation sequencing is widely used in cancer to profile tumors and detect variants, most somatic variant callers used in these pipelines identify variants at the lowest possible granularity, single-nucleotide variants (SNV). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variants (MNV). With this approach, the amino acid change from the individual SNV within a codon could be different from the amino acid change based on the MNV that results from combining SNV, leading to incorrect conclusions about the downstream effects of the variants. Here, we analyzed 10,383 variant call files (VCF) from the Cancer Genome Atlas (TCGA) and found 12,141 incorrectly annotated MNVs. Analysis of seven commonly mutated genes from 178 studies in cBioPortal revealed that MNVs were consistently missed in 20 of these studies, whereas they were correctly annotated in 15 more recent studies. At the BRAF V600 locus, the most common example of MNV, several public datasets reported separate BRAF V600E and BRAF V600M variants instead of a single merged V600K variant. VCFs from the TCGA Mutect2 caller were used to develop a solution to merge SNV to MNV. Our custom script used the phasing information from the SNV VCF and determined whether SNVs were at the same codon and needed to be merged into MNV before variant annotation. This study shows that institutions performing NGS sequencing for cancer genomics should incorporate the step of merging MNV as a best practice in their pipelines. Significance: Identification of incorrect mutation calls in TCGA, including clinically relevant BRAF V600 and KRAS G12, will influence research and potentially clinical decisions.

Abstract: Background: Inhibition of immune-checkpoint targets including PD1 is clinically effective in a variety of cancers. However, only a subset of patients respond and complete response remains uncommon. To understand the mechanisms of response and resistance, recent studies have focused on neoantigens, copy-number alterations, and transcriptional signatures of tumor tissues collected from patients treated with immune-checkpoint inhibitors. Given the known role of metabolites in modulating immunity, we sought to understand how individual patients' metabolic activities adapt to PD1 immune checkpoint blockade and how they associate with therapeutic benefits. Methods: We profiled 106-202 metabolites in pre- and multiple on-treatment patient serum samples from three independent immunotherapy trials using liquid chromatography-mass spectrometry. These metabolites are involved in the metabolism of amino acids, nucleotides, nitrogen, and lipids, among others. Our study consisted of two Phase 1 trials (CA209-038 and -009) which included 78 patients with advanced melanoma and 91 patients with metastatic renal cell carcinoma (RCC) treated with nivolumab. RNASeq was performed on matched pre- and on-treatment tumor biopsies from the melanoma cohort. To investigate the generalizability of our results, we also performed metabolomics and serum specimens from a large randomized Phase 3 trial (CheckMate 025) with 743 RCC patients, among which 394 received nivolumab and 349 received everolimus. Results: During treatment with nivolumab, kynurenine, a product of tryptophan catabolism and the IDO/TDO genes, was the most significantly changed metabolite at week 4 and at week 6 compared to pre-treatment levels among melanoma patients (37% and 34% increase on average, q=1 × 10-10 and q=1 × 10-8 respectively, paired t-test). By using Kyn/Trp (Kynurenine/Tryptophan) as a metric indicating tryptophan-kynurenine conversion, we found that this ratio falls in a range spanning approximately 8-fold among these patients, suggesting prominent individual-to-individual differences. Specifically, 78% patients had any increases and 26.5% patients had increases above 50% at week 4. We confirmed this significant kynurenine up-regulation following nivolumab treatment in RCC patients in the phase 1 and phase 3 trials. In particular, the phase 3 cohort showed 23% and 24% increase on average at week 4 and week 8 respectively (q=1 × 10-10 and q=1 × 10-12, paired t-test). Additionally, 69.4% and 8.2% patients had Kyn/Trp increases above zero and 50% respectively at week 4. Notably, patients receiving everolimus control treatment had a decrease in kynurenine (q=1 × 10-5, t-test). Kynurenine is synthesized during tryptophan catabolism by indoleamine-2,3-dioxygenase (IDO) or tryptophan dioxygenase (TDO), and has been shown to suppress anti-tumor immune responses. To explore whether the circulating Kyn/Trp correlates with immune-suppression in the tumor microenvironment, we analyzed RNAseq data of matched tumor biopsies from the CA209-038 melanoma trial. We found a significant correlation between the Kyn/Trp ratio and PD-L1 expression, 4 weeks after starting nivolumab treatment (Pearson, p=0.01). We also discovered a correlation between Kyn/Trp and IDO1 but not TDO mRNA levels at the same time point. In contrast, Kyn/Trp was not associated with prior anti-CTLA4 treatment, or tumor mutational load. Moreover, compared to all other metabolites, increases of the Kyn/Trp ratio in the melanoma cohort (week 4 vs baseline) were consistently associated with greater risks for death (p=1.2*10-4, HR=2.71, 95% CI, 1.63-4.51). In particular, patients with a & gt;50% increase in Kyn/Trp had a median OS of 15.7 months while those with decreases had a median survival time of & gt; 38 months (p = 6.0*10-5, log-rank test). In contrast, the baseline Kyn/Trp ratio did not significantly associate with the melanoma patients' overall survival. To confirm this result, the association between Kyn/Trp ratios and overall survival in the larger phase 3 trial in RCC (CheckMate 025) was evaluated using serum samples collected at different time points. We found that at baseline, higher Kyn/Trp ratios associated with shorter overall survival both for the nivolumab- and the everolimus-treated patients (p = 3.6*10-4, HR=1.79, 95% CI, 1.30-2.47; p = 1.7*10-5, HR=2.06, 95% CI, 1.48-2.85; Cox model). However, at week 4, Kyn/Trp significantly associated with overall survival only in the nivolumab arm (p = 4.7*10-4, HR=2.81, 95% CI, 1.57-5.01; Cox model) but not in the everolimus arm (p = 0.53, HR=0.76, 95% CI, 0.32-1.78; Cox model). For nivolumab-treated RCC patients, those with a & gt;50% increases of Kyn/Trp had a median survival of 16.7 months while those with any Kyn/Trp decreases had a median survival of 31.3 months (p = 4.3*10-4, log-rank test).Conclusions: We identified increased tryptophan to kynurenine conversion in response to PD1 blockade in a subset of melanoma and RCC patients. By using independent cohorts, we showed that Kyn/Trp temporal alterations robustly correlated with overall survival of patients receiving nivolumab. Our findings illustrate that checkpoint blockade in combination with IDO/TDO inhibitors might only benefit a selected group of patients with checkpoint-inhibition-triggered kynurenine pathway activation. Given the lack of improved therapeutic outcomes with PD1 and selective IDO1 inhibition among unselected patient populations in a recent phase 3 trial, our findings highlight the need and feasibility of patient stratification by monitoring serum Kyn/Trp alterations, show that kynurenine signaling may still be a relevant therapeutic target and more generally point to the relevance of metabolic adaptations in cancer immunotherapy. Our findings highlight the need and feasibility of patient stratification by monitoring serum Kyn/Trp alterations and point to the relevance of metabolic adaptations in cancer immunotherapy. Citation Format: Haoxin Li, Kevin Bullock, Carino Gurjao, David Braun, Sachet A. Shukla, Dominick Bosse, Aly-Khan A. Lalani, Shuba Gopal, Chelsea Jin, Christine Horak, Megan Wind-Rotolo, Sabina Signoretti, David F. McDermott, Gordon J. Freeman, Eliezer M. Van Allen, Stuart L. Schreiber, Frank Stephen Hodi, William R. Sellers, Levi A. Garraway, Clary B. Clish, Toni K. Choueiri, Marios Giannakis. Metabolomic adaptations and correlates of survival to immune checkpoint blockade [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr NG13.

Abstract: Background: Ipilimumab is an immune checkpoint inhibitor used to treat melanoma. Although the development of immune-related adverse events (irAEs) among patients treated with ipilimumab is well documented, little is known about factors that may increase risk of irAEs. We conducted a genome-wide association study (GWAS) to examine the genetic susceptibility to irAEs in response to ipilimumab monotherapy. Methods: In partnership with Bristol Myers Squibb BMS, extant genotype data and clinical information were obtained on melanoma patients treated with ipilimumab monotherapy from three clinical trials. Only patients who were treatment naïve were included in our analyses. We defined our outcome as the occurrence of a serious irAE, grade 3 or higher. We first analyzed data from 294 subjects, 79 with severe irAE, enrolled on CA184-169 for whom genotyping was completed using the Affymetrix 6 array. After appropriate quality control, SNP associations were determined using logistic regression models that were adjusted for ancestry, ECOG status, ipilimumab dosage (3 mg/kg vs 10 mg/kg), and number of doses ( & lt;4 vs 4+). Next, we analyzed data from 175 subjects, 63 with severe irAE, enrolled on CA209-067 or CA209-069 for whom genotyping was completed using the Illumina MegaEX array; and SNP associations were similarly determined after adjustment for ancestry, trial, and number of doses ( & lt;4 vs 4+). Summary statistics from the two analyses were combined using a fixed-effect meta-analysis. Because of the small sample size, we used a sub-genome-wide significance level of 1 × 10-5 to indicate potentially important findings. Results: The most statistically significant marker (rs55981606, p=1.39 × 10-7) and a second independent marker (rs72712605, p=6.33 × 10-6) mapped to a non-coding region on chromosome 9. We identified a marker (rs65949485, p = 9.38 × 10-6) intragenic between the SHQ1 and GXYLT2 genes, both of which are involved in the Notch signaling pathway. Markers proximal to NR2F2 (rs13270533, p=7.8 × 10-6) and within SAMD12 (rs13270533, p = 9.23 × 10-6) were also identified; the latter two genes have been implicated as being oncogenic. Additionally, we identified several markers implicating genes involved in inflammation, specifically macrophage activation, including TLE1 (rs3739581, p = 9.25 × 10-7), SLC16A4 (rs2271885, p=9.23 × 10-6) and CYP2J2 (rs427970, p=2.03 × 10-6). Conclusions: Results from our meta-analysis suggest that genes related to inflammation processes and those with known contributions to oncogenesis may play a role in the development of severe irAEs resulting from ipilimumab monotherapy. If further validated, these findings may provide the foundation to advance models to discriminate patients with a high likelihood of suffering irAE allowing for heightened surveillance of symptom onset or joint decision making for alternative therapies. Citation Format: John Pluta, Lu Qian, Kurt D'Andrea, Chunzhe Duan, Benita Weathers, Megan Wind-Rotolo, Peter Kanetsky, Katherine Nathanson. Genetic susceptibility to immune-related adverse events among melanoma patients treated with ipilimumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1352.

Abstract: Immune-related RECIST (irRECIST) were designed to capture atypical responses seen with immunotherapy. We hypothesized that, in patients with metastatic clear cell renal cell carcinoma (mccRCC), candidate biomarkers for nivolumab response would show improved association with clinical endpoints capturing atypical responders (irRECIST) compared with standard clinical endpoints (RECISTv1.1). Experimental Design: Endpoints based on RECISTv1.1 [objective response rate (ORR)/progression-free survival (PFS)] or irRECIST [immune-related ORR (irORR)/immune-related PFS (irPFS)] were compared in patients enrolled in the CheckMate-010 trial. Pretreatment tumors were analyzed by PD-L1 and PD-L2 IHC, and by multiplex immunofluorescence for CD8, PD-1, TIM-3, and LAG-3. T-cell activation signatures were assessed by RNA sequencing. Results: Median irPFS was significantly longer than median PFS. irORR was not significantly different from ORR, but immune-related progressive disease (irPD) rate was significantly lower than progressive disease (PD) rate. Tumor cell (TC) PD-L1 expression was not associated with PFS or ORR, but patients with TC PD-L1 ≥1% had longer median irPFS and higher irORR. High percentage of CD8+ tumor-infiltrating cells (TIC) that are PD-1+TIM-3−LAG-3− (% CD8+PD-1+TIM-3−LAG-3− TIC) correlated with high levels of T-cell activation and was associated with longer median irPFS and higher irORR. Notably, combination of TC PD-L1 expression with % CD8+PD-1+TIM-3−LAG-3− TIC identified three groups of patients for which irPFS and irORR were significantly different. Conclusions: Atypical responders to nivolumab were identified in the CheckMate-010 trial. We observed improved association of candidate biomarkers for nivolumab response with endpoints defined by irRECIST compared with RECISTv1.1. TC PD-L1 expression in combination with PD-1 expression on CD8+ TIC may predict outcome on nivolumab in mccRCC.