Leandro M. Colli

Burden of Nonsynonymous Mutations among TCGA Cancers and Candidate Immune Checkpoint Inhibitor Responses.

Immune checkpoint inhibitor treatment represents a promising approach toward treating cancer and has been shown to be effective in a subset of melanoma, non-small cell lung cancer (NSCLC), and kidney cancers. Recent studies have suggested that the number of nonsynonymous mutations (NsM) can be used to select melanoma and NSCLC patients most likely to benefit from checkpoint inhibitor treatment. It is hypothesized that a higher burden of NsM generates novel epitopes and gene products, detected by the immune system as foreign. We conducted an assessment of NsM across 7,757 tumor samples drawn from 26 cancers sequenced in the Cancer Genome Atlas (TCGA) Project to estimate the subset of cancers (both types and fractions thereof) that fit the profile suggested for melanoma and NSCLC. An additional independent set of 613 tumors drawn from 5 cancers were analyzed for replication. An analysis of the receiver operating characteristic curves of published data on checkpoint inhibitor response in melanoma and NSCLC data estimates a cutoff of 192 NsM with 74% sensitivity and 59.3% specificity to discriminate potential clinical benefit. Across the 7,757 samples of TCGA, 16.2% displayed an NsM count that exceeded the threshold of 192. It is notable that more than 30% of bladder, colon, gastric, and endometrial cancers have NsM counts above 192, which was also confirmed in melanoma and NSCLC. Our data could inform the prioritization of tumor types (and subtypes) for possible clinical trials to investigate further indications for effective use of immune checkpoint inhibitors, particularly in adult cancers. Cancer Res; 76(13); 3767-72. ©2016 AACR.

Functional characterization of the 12p12.1 renal cancer-susceptibility locus implicates BHLHE41

Genome-wide association studies have identified multiple renal cell carcinoma (RCC) susceptibility loci. Here, we use regional imputation and bioinformatics analysis of the 12p12.1 locus to identify the single-nucleotide polymorphism (SNP) rs7132434 as a potential functional variant. Luciferase assays demonstrate allele-specific regulatory activity and, together with data from electromobility shift assays, suggest allele-specific differences at rs7132434 for AP-1 transcription factor binding. In an analysis of The Cancer Genome Atlas data, SNPs highly correlated with rs7132434 show allele-specific differences in BHLHE41 expression (trend P value=6.3 × 10−7). Cells overexpressing BHLHE41 produce larger mouse xenograft tumours, while RNA-seq analysis reveals that constitutively increased BHLHE41 induces expression of IL-11. We conclude that the RCC risk allele at 12p12.1 maps to rs7132434, a functional variant in an enhancer that upregulates BHLHE41 expression which, in turn, induces IL-11, a member of the IL-6 cytokine family.

Landscape of Combination Immunotherapy and Targeted Therapy to Improve Cancer Management

Cancer treatments composed of immune checkpoint inhibitors and oncogene-targeted drugs might improve cancer management, but there has been little investigation of their combined potential as yet. To estimate the fraction of cancer cases that might benefit from such combination therapy, we conducted an exploratory study of cancer genomic datasets to determine the proportion with somatic mutation profiles amenable to either immunotherapy or targeted therapy. We surveyed 13,349 genomic profiles from public databases for cases with specific mutations targeted by current agents or a burden of exome-wide nonsynonymous mutations (NsM) that exceed a proposed threshold for response to checkpoint inhibitors. Overall, 8.9% of cases displayed profiles that could benefit from combination therapy, which corresponded to approximately 11.2% of U.S. annual incident cancer cases. Frequently targetable mutations were in PIK3CA, BRAF, NF1, NRAS, and PTEN We also noted a high burden of NsM in cases with targetable mutations in SMO, DDR2, FGFR1, PTCH1, FGFR2, and MET Our results indicate that a significant proportion of solid tumor patients are eligible for immuno-targeted combination therapy, and they suggest prioritizing specific cancers for trials of certain targeted and checkpoint inhibitor drugs. Cancer Res; 77(13); 3666-71. ©2017 AACR.

Abstract 2333: Possible prediction of tumor specific checkpoint inhibitor response based on TCGA somatic mutation load

Immune checkpoint inhibitor therapy has been shown to be effective in a subset of patients with melanoma, non-small cell lung cancer (NSCLC) and kidney cancer. Recent studies have suggested that the number of non-synonymous mutations (NsM) can be used to select melanoma and NSCLC patients most likely to benefit from immune checkpoint inhibitor treatment. It is hypothesized that NsMs generate novel epitopes and gene products which can be detected by the immune system. The aim of this study is to apply prior information on NsM count and immune checkpoint inhibitor treatment to a range of tumor subtypes in the TCGA database to evaluate the proportion cases that could be possible responders. In our analysis of published studies of melanoma and NSCLC, the receiver operator characteristic (ROC) curve suggests a cutoff of 192 NsM would have a maximum combination of sensitivity (74%) and specificity (59.3%) for potential clinical benefit for patients. We conducted an analysis of 7,757 samples from 26 different TCGA tumor types and observed that approximately 16.2% of TCGA samples harbor more than 192 NsM, and thus could be in the category associated with a higher likelihood of response to immune checkpoint inhibitors. Based on NsM count, bladder, colon, gastric, and endometrial cancers each contained more than 30% of tumors with a high NsM and thus, could be possible candidates for checkpoint immune therapy. Although our model estimates clinical response to immune checkpoint treatment from NsM count is preliminary and needs future validation, information on NsM count can be useful for selecting tumor types most likely to benefit in clinical trials of immune checkpoint inhibitor treatment. Citation Format: Leandro Machado Colli, Mitchell J. Machiela, Timothy Myers, Lea Jessop, Kai Yu, Stephen J. Chanock. Possible prediction of tumor specific checkpoint inhibitor response based on TCGA somatic mutation load. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2333.

Abstract 5061: Post-GWAS functional characterization of the 12p11.23 renal cancer susceptibility locus implicates BHLHE41

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Introduction. Two of common variants, rs718314 and rs1049380, were associated with renal cell carcinoma (RCC) at the 12p11.23 locus. Interestingly, rs718314 was also identified as being associated with waist-hip ratio. The objective of the present study is to perform a functional analysis of the 12p11.23 region in relation to RCC risk. Materials and methods. We performed an imputation analysis within 1 Mb of rs718314 in three different study populations from a previously published GWAS of RCC (4197 cases and 8527 controls). The genotyped and high-quality imputed SNPs were tested for association with RCC. We examined the significantly associated variants for sequence overlap with potential regulatory sites by cross referencing them with ENCODE data. Selected putatively functional SNPs were tested for enhancer activity using a dual luciferase assay in 3 different renal cell lines (UO31, SN12-C, 786-O) and electro-mobility shift assays (EMSA) were used to look for binding of transcription factors to selected SNPs. In addition, the RCC-associated variants present in the TCGA database were examined for an effect on nearby gene expression (ITPR2, SSPN, BHLHE41). Results. After meta-analysis, 499 of the total 13,159 genotyped and imputed SNPs had association p-values with RCC less than 0.05. Within this group, 44 SNPs demonstrated nominally significant association with RCC risk (p<5.10-5). The two initial GWAS SNPs, rs718314 and rs1049380, were strongly associated with RCC (Padj = 3.44.10-6 and Padj = 5.27.10-6). All nominally significant SNPs were in a non-coding region which contains the 3′-UTR of ITPR2. Six of the 44 variants were in regions enriched for H3K4me1 and H3K27ac, chromatin marks found in enhancers. Only one SNP, rs7132434 which is highly correlated with the initial GWAS signal (rs718314, r2=1), showed allele specific regulatory activity in luciferase assays and allele specific differences in protein binding by EMSA. Five SNPs associated with RCC were present in the TCGA database. All of them were associated with BHLHE41 expression in tumor tissues (p<0.05). The most significant association was found with rs12814794 (p=1.10-8) which is in high linkage disequilibrium with rs718314 (r2=0.956) and rs7132434 (r2=0.956). There was no association between RCC associated SNPs and SSPN or ITPR2 tissue expression. BHLHE41 is a gene which has been recently been shown to be involved in the VHL/HIF pathway in breast cancer. It is also known to regulate adipogenic differentiation and could be a link between RCC and obesity, a known risk factor for RCC. Conclusion. Our results suggest rs7132434 is the functional SNP responsible for the GWAS signal and that this locus could act as an enhancer of BHLHE41. Further investigations will be necessary to confirm the link between rs7132434 and BHLHE41 and to understand the role of BHLHE41 in renal carcinogenesis. Citation Format: Lea Jessop, Pierre Bigot, Mitchell Machiela, Timothy Myers, Nilabja Sikdar, Leandro Colli, Stephen Chanock. Post-GWAS functional characterization of the 12p11.23 renal cancer susceptibility locus implicates BHLHE41. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5061. doi:10.1158/1538-7445.AM2014-5061