Association Of Tumor Mutational Burden Research Articles

Validation of 3-factor clinical-genomic model to predict response to atezolizumab as first-line or post-platinum therapy for advanced urothelial carcinoma.

552 Background: Previously, we reported a 3-factor model including tumor mutation burden (TMB), peripheral blood neutrophil/lymphocyte ratio (NLR) and visceral metastasis status to predict tumor regression (c-statistic=0.90) when using ICIs for mUC regardless of line of therapy. We conducted an external validation of this model to determine its ability to predict response. Methods: We utilized data from a phase II trial, IMvigor210, which evaluated atezolizumab (atezo) for post-platinum pts or as first-line therapy for cisplatin-ineligible pts with mUC. Pts with TMB, NLR, visceral metastasis and RECIST1.1 response status available were evaluable. Tumor genomic analysis was performed using FoundationOne, which sequences 324 cancer-related genes. Multivariable regression studied the association of TMB (<10 vs. ≥10 mutations/megabase), NLR (<5 vs. ≥5) and visceral metastasis status (yes vs.no) with RECIST 1.1 response status (≥partial response [PR] vs no PR). Model discrimination performance was assessed using the concordance (c)-index. Results: A total of 234 pts were evaluable for analysis, of whom 185 (79%) were men. 164 (70.1%) pts received post-platinum therapy and 70 (29.9%) received first-line therapy with atezo. 60 pts exhibited RECIST 1.1 ≥PR. On multivariate analysis, all 3 factors were independently and significantly associated with ≥PR: TMB ≥10 mutations/megabase (HR -4.254, p=2.1 x 10−5), low NLR (HR=2.591, p=0.00958) and absence of visceral metastasis status (HR=4.105, p=4.04 x 10−5). The c-index of this 3-factor model to predict ≥PR was 0.77. Presence of all 3 favorable factors (TMBhigh, NLRlow, no visceral metastases) was associated with ≥PR in 15/21 pts (71.4%), while the absence of all 3 factors (TMBlow, NLRhigh, visceral metastases) was associated with ≥PR in 2/37 pts (5.4%). Conclusions: A 3-factor model combining readily available clinical and genomic variables including TMB, NLR and visceral metastasis status was validated to robustly predict RECIST 1.1 response in pts with mUC receiving atezo as first-line or post-platinum therapy. This model may improve the therapeutic index and cost efficacy of atezo.

Tumor mutational burden in lung cancer: a systematic literature review.

Purpose: To assess the association of tumor mutational burden (TMB) with clinical outcomes, other biomarkers and patient/disease characteristics in patients receiving therapy for lung cancer. Results: In total, 4,303 publications were identified; 81 publications were included. The majority of publications assessing clinical efficacy of immunotherapy reported an association with high TMB, particularly when assessing progression-free survival and objective response rate. High TMB was consistently associated with TP53 alterations, and negatively associated with EGFR mutations. High TMB was also associated with smoking, squamous cell non-small cell lung carcinoma, and being male. Methods: A systematic literature review based upon an a priori protocol was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane methodologies. Searches were conducted in EMBASE, SCOPUS, Ovid MEDLINE®, and Emcare (from January 2012 until April 2018) and in two clinical trial registries. Conference abstracts were identified in EMBASE, and in targeted searches of recent major conference proceedings (from January 2016 until April 2018). Publications reporting data in patients receiving therapy for lung cancer that reported TMB and its association with clinical efficacy, or with other biomarkers or patient/disease characteristics, were included. Results are presented descriptively. Conclusion: This systematic literature review identified several clinical outcomes, biomarkers, and patient/disease characteristics associated with high TMB, and highlights the need for standardized definitions and testing practices. Further studies using standardized methodology are required to inform treatment decisions.

In-house Implementation of Tumor Mutational Burden Testing to Predict Durable Clinical Benefit in Non-small Cell Lung Cancer and Melanoma Patients.

Tumor mutational burden (TMB) has emerged as an important potential biomarker for prediction of response to immune-checkpoint inhibitors (ICIs), notably in non-small cell lung cancer (NSCLC). However, its in-house assessment in routine clinical practice is currently challenging and validation is urgently needed. We have analyzed sixty NSCLC and thirty-six melanoma patients with ICI treatment, using the FoundationOne test (FO) in addition to in-house testing using the Oncomine TML (OTML) panel and evaluated the durable clinical benefit (DCB), defined by >6 months without progressive disease. Comparison of TMB values obtained by both tests demonstrated a high correlation in NSCLC (R2 = 0.73) and melanoma (R2 = 0.94). The association of TMB with DCB was comparable between OTML (area-under the curve (AUC) = 0.67) and FO (AUC = 0.71) in NSCLC. Median TMB was higher in the DCB cohort and progression-free survival (PFS) was prolonged in patients with high TMB (OTML HR = 0.35; FO HR = 0.45). In contrast, we detected no differences in PFS and median TMB in our melanoma cohort. Combining TMB with PD-L1 and CD8-expression by immunohistochemistry improved the predictive value. We conclude that in our cohort both approaches are equally able to assess TMB and to predict DCB in NSCLC.

Abstract CT037: Genomic analyses and immunotherapy in advanced melanoma

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.

Integrative molecular analysis of metastatic Merkel cell carcinoma to identify predictive biomarkers of response to avelumab.

9569 Background: Avelumab, an FDA-approved human anti–PD-L1 IgG1 monoclonal antibody for patients (pts) with metastatic Merkel cell carcinoma, showed an objective response rate (ORR; by RECIST v1.1) of 31.8% in a second-line phase 2 trial (NCT02155647). We assessed the association of tumor mutational burden (TMB; nonsynonymous somatic variants/megabase), PD-L1 expression, Merkel cell polyomavirus (MCPyV) status, and CD8+ tumor-infiltrating T-cell density with ORR and survival. Molecular profiles (RNAseq and WEX) also were analyzed. Methods: Baseline tumors (n = 36) were profiled using RNAseq and WEX sequencing. PD-L1 expression (≥1% cutoff), MCPyV status, and CD8+ T-cell density at the tumor invasive margin were evaluated by IHC. MHC locus expression was measured with OptiType and loss of heterozygosity (LOH) with LOHHLA. Results: Of 36 pts profiled, 12 had a response, 27 were PD-L1+, and 23 were MCPyV+. The TMB upper tertile and quartile values were 1.34 and 3.16, respectively. Consistent with literature, MCPyV− pts had a higher median TMB (2.72) than MCPyV+ pts (0.49). PD-L1+ tumors trended toward a higher TMB. An empirical cohort-specific TMB cutoff of ≥2 was chosen to include sufficient pts per subgroup. Pts with TMB ≥2 vs TMB < 2 had higher ORR (5 of 11 [45.5%] vs 7 of 25 [28.0%]) and 6-mo PFS rates (60% vs 38%). Among pts with TMB ≥2, the highest ORRs were reported in MCPyV− (4 of 7 pts), PD-L1+ (5 of 9 pts), and CD8+ T-cell density higher than median (5 of 6 pts) subgroups. MHC expression trended with ORR and survival. Higher mean MHC expression was found in pts with CD8+ T-cell density higher than median (p < 0.05). Mutations in antigen presentation genes were detected: LOH at the HLA locus in 9 of 30 pts (28%), including 4 with a response; an NK cell activation signature was also associated with response. These data may suggest that ADCC contributes to response. Factorial analysis of gene signature scores identified signatures (eg, IFNγ, TP53 pathway) associated with MCPyV status and response. Conclusions: Responses in this data set were not attributed to any specific biomarker alone. Future analysis is focused on validating these results and identifying rational drug combinations with avelumab. Clinical trial information: NCT02155647.

Association of Tumor Mutational Burden With DNA Repair Mutations and Response to Anti–PD-1/PD-L1 Therapy in Non–Small-Cell Lung Cancer

PurposeTo examine clinical predictors of tumor mutational burden (TMB), to explore the association between TMB and DNA repair mutations, and to analyze TMB as a biomarker for response to immune checkpoint blockade in non–small-cell lung cancer. Patients and MethodsTMB scores were determined retrospectively for 72 consecutive patients at our institution with next-generation sequencing comprehensive genomic profiling testing by Foundation Medicine. TMB scores were correlated with a number of clinical variables and presence of DNA repair mutations. Thirty-four patients were treated with anti–programmed cell death 1 (PD-1)/programmed death ligand 1 (PD-L1) therapies, and survival analyses based on TMB score were performed. In addition, tissue immunohistochemical analysis was performed for a subset of patients. ResultsHistory of smoking, but not other clinical variables, including prior treatment lines, stage of disease, and number of metastatic sites, predicted higher TMB score. Higher TMB score was significantly associated with greater number of DNA repair mutations. In the subset of patients treated with immune checkpoint blockade, higher TMB score significantly predicted overall survival, but not progression-free survival (hazard ratio = 0.10, P = .003; hazard ratio 1.1, P = .84, respectively). In a small subset of patients, PD-1/PD-L1 staining did not independently predict progression-free survival or overall survival. ConclusionTissue TMB was significantly associated with smoking history and number of DNA repair mutations. TMB is a promising biomarker for response to anti–PD-1/PD-L1 therapy, with higher TMB score predicting longer overall survival.

Abstract 658: Association of tumor mutational burden (TMB) with DNA repair mutations and response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer (NSCLC)

Abstract Background: Identifying optimal biomarkers for response to anti-PD-1/PD-L1 therapies in non-small cell lung cancer (NSCLC) is critical. Tumor mutational burden (TMB) is a potential biomarker of genomic instability and neoantigen binding sites to activated effector T cells. The goal of this study was to examine the association of TMB with overall survival for patients treated with checkpoint blockade and to correlate TMB with mutational status, including DNA repair mutations. Methods: We retrospectively examined TMB using next-generation sequencing (FoundationOne) for 82 patients with NSCLC in our institution. TMB included coding base substitutions and indel alterations, but excluded potentially functional mutations. TMB high versus low was stratified based on 15 mutations per megabase pair. We correlated TMB with DNA repair mutations, mutational status, and smoking history. In addition, survival data were obtained for 35 patients who were treated with anti-PD-1/PD-L1 therapy. Results: TMB was associated with significantly longer overall survival for patients treated with checkpoint blockade (Table 1, p < 0.04). In addition, TMB was independently correlated with direct and indirect (Chae et al. 2016) DNA repair mutations (p < 0.03). TMB was also significantly associated with smoking, number of coding region mutations, and treatment with at least two prior lines of therapy (p < 0.02). A trend toward lower TMB was found for patients with mutations in EGFR, ALK, or KRAS (p = 0.06). Conclusions: Higher TMB was associated with improved survival for patients treated with anti-PD-1/PD-L1 therapies. In addition, TMB was correlated with DNA repair mutations, number of coding mutations, prior treatment, and smoking. Our results indicate that TMB can be used as a biomarker for response to checkpoint blockade in NSCLC. Table 1.Tumor mutational burden (TMB) by patient characteristic and mutation statusPatient CharacteristicTMB (mutations per megabase)PTMB (<15)TMB (≥15)AllSmoking HistoryMinimal/Never (N)25126P = 0.011+Current/Former (N)381856All (N)631982Number of Treatment Lines Prior to Checkpoint Blockade (Excluding Targeted Therapy)0-1 (N)20424P = 0.017+2+ (N)4711All (N)241135Presence of EGFR/ALK/KRAS MutationsYes27330P = 0.061+No361652All (N)631982Number of Potentially Functional Direct + Indirect DNA Repair MutationsMean (N)0.76 (N=63)1.26 (N=19)0.88 (N=82)P = 0.027*Number of VUS Direct + Indirect DNA Repair MutationsMean (N)1.30 (N=63)2.26 (N=19)1.52 (N=82)P = 0.011*Number of Direct DNA Repair MutationsMean (N)1.08 (N=63)2.42 (N=19)1.39 (N=82)P = 0.001*Number of Total DNA Repair MutationsMean (N)2.06 (N=63)3.53 (N=19)2.40 (N=82)P = 0.005*Number of Potentially Functional MutationsMean (N)4.79 (N=63)8.00 (N=19)5.54 (N=82)P = 0.002^Number of VUS MutationsMean (N)9.13 (N=63)25.00 (N=19)12.80 (N=82)P < 0.001^Total Reported MutationsMean (N)13.92 (N=63)33.00 (N=19)18.34 (N=82)P < 0.001^Overall SurvivalKaplan-Meier Log-Rank TestP = 0.020Cox Proportional Hazards Regression ModelHR = 0.1995% CI: [0.04 - 0.88]P = 0.034VUS, Variant of Unknown Significance; HR, Hazard Ratio; + Pearson’s Chi-Squared; * Logistic regression; ^ Welch’s two-sample t-test Citation Format: Andrew A. Davis, Young Kwang Chae, Sarita Agte, Alan Pan, Nisha Mohindra, Victoria Villaflor, Kirtee Raparia, Francis J. Giles. Association of tumor mutational burden (TMB) with DNA repair mutations and response to anti-PD-1/PD-L1 therapy in non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 658. doi:10.1158/1538-7445.AM2017-658

Association of tumor mutational burden in cutaneous squamous cell carcinoma with genomic alterations in Notch family receptors.

e13031 Background: In Cutaneous Squamous Cell Carcinoma (cSqCC), Notch1, Notch2, and Notch3 have been identified as tumor suppressors with a high rate of inactivating mutations early in cSqCC pathogenesis. Despite the high frequency of alterations, the biologic and therapeutic implications of Notch genomic alterations (GAs) in cSqCC are incompletely understood. Methods: 232 FFPE samples of cSqCC were evaluated by comprehensive genomic profiling (CGP) of 315 genes and analyzed for all classes of GAs, with diagnoses confirmed by central pathology review. Notch GAs with unknown functional impact were excluded. Tumor mutational burden (TMB) was calculated from 1.11 Mb of sequenced DNA and reported as mutations/Mb. Results: The cohort of 232 samples was 78% male and 22% female, aged from 17 to 88, with confirmed metastatic disease in 32% of cases. 115 (50%) samples had a Notch family member GA with a known or predicted functional impact. 96 cases had Notch1 GAs, 43 cases had Notch2 GAs, and 14 cases had Notch3 GAs with 40 cases having GAs in multiple Notch family members. These mutations were 41% missense, 34% nonsense, 15% splice site, 9% frameshift indels, and 1% non-frameshift indels alterations. Patients with Notch GAs were significantly older (median 70 years old vs median 64, p < 0.01). TMB was increased among samples with Notch GAs (median TMB of 63 mutations/mb versus 20 mutations/mb, p < 1x10-6), with similar differences for primary and metastatic samples. Cases with Notch GAs had more total GAs per case (mean 10.4 vs 7.4, p < 1.5x10-10); however, the top co-mutated genes were the same (TP53, CDKN2A, FAT1, MLL2). Both groups had a high proportion of C- > T/G- > A transitions, consistent with UV damage; however, the proportion was higher in cases with Notch GAs (median 83% vs 80%) - a difference seen in primary and metastatic samples. Conclusions: 50% of cSqCC cases had a Notch family member loss of function GA, which was associated with increased TMB in the primary and metastatic setting. With pre-clinical models and case studies showing responses to PD-1 inhibitors in cSqCC, further investigations are warranted into the associations of Notch GAs with mutational burden and response to immunotherapy.

Association of tumor mutational burden with smoking and mutation status in non-small cell lung cancer (NSCLC).

24 Background: Reponses to immunotherapy have been observed in multiple solid tumors including non-small cell lung cancer (NSCLC). Identifying optimal biomarkers for response to anti-PD-1/PD-L1 therapies remains critical. Tumor mutational burden (TMB) may indicate genomic instability and potential neoantigen binding sites to activated effector T cells. Methods: We retrospectively examined tumor mutational burden (TMB) using next-generation sequencing (Foundation Medicine) for 83 patients with NSCLC in our institution. TMB included both coding and non-coding regions, but excluded potentially functional mutations. We correlated TMB (mutations per megabase) with smoking history, number of potentially functional mutations, variants of unknown significance, and the driver mutations EGFR, ALK, and KRAS. TMB high versus low was stratified based on 15 mutations per megabase pair. Results: Our findings demonstrated that TMB was significantly associated with current/former smoking status (p = 0.01, Table 1). TMB was also significantly associated with number of potentially functional mutations, number of variants of unknown significance (VUS), and total reported mutations (p < 0.01). The absence of mutations in EGFR, ALK, or KRAS tended to be associated with higher TMB as well (p = 0.07). Conclusions: TMB was associated with smoking status, as well as potentially functional mutations, VUS, and total number of reported mutations. Our results indicate that number of coding region mutations predict genomic instability in non-coding regions. Future studies are needed to correlate this measure with other immune biomarkers and patient outcome in NSCLC. [Table: see text]