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Purpose: Patients ≥18 months of age with International Neuroblastoma Staging System (INSS) stage 3 unfavorable histology (UH), MYCN-nonamplified (MYCN-NA) tumors have favorable survival rates compared with other high-risk neuroblastoma populations. The impact of select clinical and biological factors on overall survival (OS) and event-free survival (EFS) were evaluated. Experimental Design: Patients enrolled on Children's Oncology Group (COG) A3973 (n = 34), ANBL0532 (n = 27), and/or biology protocol ANBL00B1 (n = 72) were analyzed. Tumors with available DNA (n = 65) and RNA (n = 42) were subjected to whole-exome sequencing (WES) and RNA sequencing. WES analyses and gene expression profiling were evaluated for their impact on survival. Multivariate analyses of EFS/OS using significant factors from univariate analyses were performed. Results: 5-year EFS/OS for patients treated with high-risk therapy on A3973 and ANBL0532 were 73.0% ± 8.1%/87.9% ± 5.9% and 61.4% ± 10.2%/73.0% ± 9.2%, respectively (P = 0.1286 and P = 0.2180). In the A3973/ANBL0532 cohort, patients with less than partial response (PR; n = 5) at end-induction had poor outcomes (5-year EFS/OS: 0%/20.0% ± 17.9%. Univariate analyses of WES data revealed that subjects whose tumors had chromosome 1p or 11q loss/LOH and chromosome 5 or 9 segmental chromosomal aberrations had inferior EFS compared with those with tumors without these aberrations. Multivariate analysis revealed that 11q loss/LOH was an independent predictor of inferior OS [HR, 3.116 (95% confidence interval, 1.034–9.389), P = 0.0435]. Conclusions: Patients ≥18 months of age at diagnosis who had tumors with UH and MYCN-NA INSS stage 3 neuroblastoma assigned to high-risk therapy had an 81.6% ± 5.3% 5-year OS. Less than PR to induction therapy and chromosome 11q loss/LOH are independent predictors of inferior outcome and identify patients who should be eligible for future high-risk clinical trials.

Triple-negative breast cancer (TNBC) is an aggressive disease that disproportionately affects African American (AA) women. Limited targeted therapeutic options exist for patients with TNBC. Here, we employ spatial transcriptomics to interrogate tissue from a racially diverse TNBC cohort to comprehensively annotate the transcriptional states of spatially resolved cellular populations. A total of 38,706 spatial features from a cohort of 28 sections from 14 patients were analyzed. Intratumoral analysis of spatial features from individual sections revealed heterogeneous transcriptional substructures. However, integrated analysis of all samples resulted in nine transcriptionally distinct clusters that mapped across all individual sections. Furthermore, novel use of join count analysis demonstrated nonrandom directional spatial dependencies of the transcriptionally defined shared clusters, supporting a conserved spatio-transcriptional architecture in TNBC. These findings were substantiated in an independent validation cohort comprising 17,861 spatial features representing 15 samples from 8 patients. Stratification of samples by race revealed race-associated differences in hypoxic tumor content and regions of immune-rich infiltrate. Overall, this study combined spatial and functional molecular analyses to define the tumor architecture of TNBC, with potential implications in understanding TNBC disparities. Significance: Spatial transcriptomics profiling of a diverse cohort of triple-negative breast cancers and innovative informatics approaches reveal a conserved cellular architecture across cancers and identify proportional differences in tumor cell composition by race.

We propose a method to leverage spatial transcriptomics and bioinformatic analysis to identify sub-clonal loss of heterozygosity that could otherwise be missed by standard bulk sequencing in glioblastoma tumors. Glioblastomas are highly invasive and aggressive brain tumors with a low five-year survival rate of less than 10%. Current treatment strategies are not sufficient for long term disease outcome, and innovative approaches to analyze glioblastoma are imperative for future improved options. Many factors contribute to difficulty of treatment, though one critical consideration is the diffuse nature and known intratumoral heterogeneity of this cancer. It is important to determine LOH heterogeneity, as this genomic alteration is associated with copy number variation and specific classifications of gliomas. Loss of heterozygosity is an irreversible deletion of DNA that is a common alteration in cancer. Application of spatial transcriptomics can increase our understanding of genomic complexity across a tissue, and unsupervised graph clustering can computationally separate spatial regions with similar gene expression patterns. Our method investigates spatial clusters individually at known heterozygous SNP sites to identify evidence for LOH with Bayesian inference and a hidden Markov model. Our analysis centers on the balance of reference (A) and non-reference (B) spatial transcriptomics read counts at SNPs of interest. B allele frequency is the number of reads aligned to the alternative allele divided by the total number of reads counted at the SNP. At a normal two-copy state at a heterozygous site, B allele frequency is ideally 50 percent. LOH can be identified as this value deviates toward 0 or 100, and copy number alterations impact this frequency. Our method utilizes Bayes factor values, or likelihood ratios between two models, using allele counts to provide support for either LOH or a heterozygous event. For our analysis, spatial transcriptomics BAMs are processed with a graph clustering algorithm and split into cluster-specific BAMs. We calculate allele count coverage for each cluster at pre-selected heterozygous SNP positions identified through germline exome sequencing. Bayes factor values are then calculated at each SNP, resulting in evidence for LOH or a heterozygous event. Chromosomal regions are segmented by a hidden Markov approach. Cumulative metrics for each segment are evaluated to determine a “state” label of heterozygous, LOH, or undefined. We tested our method on three WHO grade 4 IDH wild-type EGFRvIII positive fresh frozen glioblastoma tissue samples. Sub-clonal heterogeneity was identified in two samples and confirmed by bulk exome sequencing, bulk RNA sequencing, and analysis of initial clinical reports. Citation Format: Michelle G. Webb, Frances Chow, Carmel McCullough, Bohan Zhang, Kyle Hurth, John Carpten, Gabriel Zada, David W. Craig. Identification of sub-clonal loss of heterozygosity (LOH) in glioblastomas analyzed with spatial transcriptomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3124.

Ovarian cancer (OvCa) is the deadliest gynecological malignancy in the United States. Surgery and chemotherapy are the primary treatments for OvCa, but 80% of late-stage OvCa patients experience chemo-resistant recurrence, which necessitates the development of new treatment strategies. The genomic diversity within a tumor and the interactions among various cell types within its microenvironment are considered key factors contributing to therapeutic efficacy. Specifically, women who harbor germline BRCA1 or BRCA2 mutations are at increased risk of developing high grade serous ovarian cancer (HGSC). To understand the genomic consequences, including somatic alterations, associated with defective DNA repair, tumor DNA and RNA was isolated from fresh frozen OCT embedded sections from 15 HGSC patients with BRCA1/2 mutation and 10 without any alterations in the BRCA genes (BRCA-wt). Whole exome sequencing (WES) and total RNA-seq was performed to determine the association of homologous recombination (HR) DNA repair gene defects with tumor mutation burden (TMB), neoantigen load (NL), and immunological assessment of tumor microenvironment. TMB was calculated from mutation rates of somatic WES. Germline exome analysis was used to validate inherited BRCA mutations. To identify the somatic mutations, somatic single nucleotide variants and InDels were detected using Strelka. TP53 mutations were most common with several other genes showing only modest mutation frequency. Mutation signatures were also detected with maftools and compared to the COSMIC mutational signature database. BRCA-mutated samples displayed a unique mutational signature associated with defects in HR DNA repair pathway. We also observed heterogeneity in copy number variation profiles amongst cases, as determined by the tool Sequenza. Furthermore, gene set enrichment analysis indicated differential enrichment of P53 pathway, MAPK pathway, and PTEN pathway, in addition to numerous pathways related to immune cell signaling and immune response. RNA-seq data was analyzed with CIBERSORTx and revealed different proportions of 22 immune effector cell types that accompany tumor cells within the HGSC microenvironment. Additional analyses are underway, including measuring differences in NL in BRCA-mutated versus BRCA-wt cases. This work will represent a significant advancement in our fundamental knowledge regarding the complexities of the TME and effective immunological responses in OvCa. Citation Format: Jing Qian, Lynda D. Roman, Seeta Rajpara, Monica Neuman, Varun Khetan, David W. Craig, Joseph Carlson, John D. Carpten. Assessing difference in the tumor and immune microenvironment of BRCA1/2 mutated versus BRCA wild type high grade serous ovarian cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6082.

Introduction: CRC is the second leading cause of cancer mortality in the United States. Clinical factors and molecular characteristics may impact therapeutics and prognosis. Scientific studies have uncovered significant aberrations, including critical genes and pathways. Despite these efforts, few studies have utilized similar sample sizes to TCGA, heterogeneous populations and integrative clinical data to compare their reported genomic changes, even though little is known about the tumor microenvironment and its significance for colorectal tumorigenesis. Methods: Clinical and DNA genomic data from 262 colorectal tumor/normal DNA samples were obtained for whole exome sequencing analysis from the Oncology Research Information Exchange Network and two colorectal tissue samples for Spatial Transcriptomics profiling from the USC colorectal cancer Moonshot project. Whole Exome Sequencing data analysis was used for identifying genetic alterations. Samples were stratified based on microsatellite instability, age group, anatomical subsites, and histological subtypes. Emphasis was given to comparing molecular characteristics among Hispanic/Latino patients since their reported higher mortality and cancer disparities. Mutation frequencies from our cohort were compared to those from the TCGA. An ongoing spatial transcriptomics analysis consists in processing two fresh-frozen tissue samples through the visium spatial gene expression library using standard short-read sequencing. Results: Tumor molecular profiling revealed 20 genes significantly mutated. We found differences in gene mutation frequencies among our samples, highlighting APC (60%), TP53 (56%), TTN (49%), and KRAS (44%) gene mutations. In comparison with TCGA data, in addition to the expected APC, TP53, PIK3CA, and KRAS mutations, we found frequent mutations in POLE and TTN. To assess the basis for the considerably different mutation rates, we evaluated MSI. Among the 262 tumors, 41 (16%) had high levels of MSI, 2 (1%) had low levels of MSI (MSI-L), and 215 (82%) were microsatellite stable (MSS). Cancer heterogeneity was reported among tumors with different characteristics such as age group, anatomical subsite, and histological subtypes. The ongoing spatial transcriptomics analysis that will be ready before the annual meeting will identify cellular populations and map immunological and inflammatory signals in the microenvironment. Conclusions: Our study reveals the impact of molecularly profiling tumors using considerable sample sizes and stratified samples in several subgroups. Our study adds important information about tumor heterogeneity and the tumor microenvironment in colorectal cancer by including our spatial transcriptomics data analysis. Citation Format: Enrique Velazquez Villarreal, Seeta Rajpara, Yuxin Jin, Jing Qian, Bohan Zhang, Brigette Waldrup, Donna Loza, Heinz-Josef Lenz, David W. Craig, John D. Carpten. Tumor molecular profiling and spatial transcriptomics to assess colorectal cancer heterogeneity and microenvironment [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1515.

Background: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer that disproportionately affects African-American and black (AAB) women, who have higher rates of incidence and mortality. To understand this disparity, we must apply advanced molecular profiling to racially diverse cohorts. We propose the use of spatial transcriptomics to map whole transcriptome data to several thousand coordinates within tissue sections, for comprehensive and unbiased characterization of TNBC tumors and their microenvironment. Methods: We applied the Visium Spatial Gene Expression method (10x Genomics) to 28 fresh frozen TNBC tissue sections obtained from 14 patients (7 AAB and 7 Non-Hispanic White). Sections were stained with H&E, and regions of tumor and stroma were annotated by a pathologist. The assay yielded whole transcriptome data from over 36,000 spatially-defined features, averaging 1,380 features per section. Expression data from each sample was normalized and subject to dimensionality reduction and clustering analysis. All sections were also integrated into a single dataset, from which integrated clusters (IC) were defined. Several bioinformatics tools were used to annotate the data at the feature, cluster, and IC level. Join count statistical analysis was employed to quantify patterns of spatial aggregation or dispersion of ICs across samples. Results: Clustering analysis revealed that all samples exhibited a great deal of heterogeneity; most contained several transcriptionally distinct regions of both tumor and stroma. Application of the ESTIMATE gene sets at the feature level accurately defined tumor and non-malignant regions when compared to histopathological annotation. Gene set enrichment analysis at the cluster level allowed further classification of biological processes within each sample. Following integration of all 28 samples, 9 ICs were defined from transcriptional data. Although all ICs were present in all samples, IC5 - characterized by a strong hypoxic signature - was overrepresented in AAB samples. ICs were then mapped back to individual samples and subject to join count statistics. This revealed strong spatial autocorrelation within each IC, as well as significant spatial pairings of ICs. The fibrotic clusters IC3 and IC7 were strongly contiguous in all samples (z-score > 5), as were tumor clusters IC1 and IC4. Conversely, we found spatial exclusion between IC3 and tumor clusters IC5 and IC2. Conclusion: Our study provides novel evidence of spatially related populations across diverse TNBC samples. Our findings suggest that, while TNBC tumors are highly heterogeneous, they exhibit elements of a common spatio-transcriptional architecture. Moreover, this provides a new framework in which to evaluate transcriptional differences between racial groups within a broader spatial context. Citation Format: Rania Bassiouni, Michael Idowu, Lee D. Gibbs, Pamela J. Grizzard, Michelle G. Webb, Ashley Noriega, Valentina Robila, David W. Craig, John D. Carpten. Comprehensive spatial transcriptomic analysis of an integrated, diverse cohort reveals distinct molecular topographic patterns in triple negative breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2032.

Introduction: Endometrial cancer (EC) is the most common gynecological malignancy among women in developed countries. In the United States, it is estimated that 66,570 new cases and 12,940 deaths will occur in 2021. EC is more common in white women, but black women have a worse prognosis with higher mortality rates. Molecular characteristics in tumor tissue have been reported for potential clinical utility. Integrated genomic characterization efforts have shown common molecular alterations occurring in oncogenic pathways from bulk molecular profiling of EC tumors. However, little is known about the tumor heterogeneity in endometrial cancer. Thus, using high resolution single cell technologies, we assessed tumor heterogeneity in endometrial cancers. Our preliminary study includes endometrial tumors from five (3 African Americans, 1 Hispanic/Latino, 1 Caucasian) cases. We utilize bulk whole exome sequencing and single cell whole genome sequencing copy number variation to study tumor heterogeneity. Frozen tumor sections were used to collect and sequence single nuclei utilizing the 10x ChromiumTM single cell copy number variation (scCNV). Illumina NovasEQ600 was used to sequence the single cell libraries. Results: 1,546 cells were sequenced across five tumors. Each tumor was visually inspected through hierarchical clustering from the scCNV data. Beyond describing the heterogeneity through chromosome or chromosome arm level gains and losses in samples that included single and mixed histology tumors, we assessed clonal populations suggesting apparently different clonal evolution within samples. Mutations in cancer related genes such as TP53, PTEN and PIK3CA among others suggested a clonal tumor cell stratification. The single cell whole genome data was compared to bulk exome sequencing data to determine the power of scCNV to detect clonal populations of tumor cells. Conclusions: Using varied histologies in five EC tumors, we performed DNA-CNV analysis using single cell sequencing. This level of resolution enhanced our analysis to provide clear evidence of heterogeneity in all tumors that were assessed in our study. We plan to further expand our sample size to study the degree of heterogeneity in endometrial cancer. Citation Format: Enrique Velazquez Villarreal, Lee D. Gibbs, Dana Mahinbakht, Diane M. Da Silva, Lynda D. Roman, David W. Craig, John D. Carpten. Single cell whole genome sequencing to assess tumor heterogeneity in endometrial cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 772.

Introduction: Endometrial cancer accounts for ~76,000 deaths amongst women worldwide. In the United States, it is estimated 65,620 new cases and 12,590 deaths occurring in 2020, being the fourth most common gynecologic malignancy in the country. It has been reported that specific molecular characteristics in tissues are associated with poorer prognosis. Publicly available data generated from bulk molecular profiling of tumors has provided a molecular taxonomy of endometrial cancers with common alterations occurring in a number of known oncogenic pathways. However, little is known about the degree of heterogeneity in endometrial cancer. Thus, we have set out to utilize single cell technologies to assess tumor heterogeneity in endometrial cancers. Methods: Our preliminary study includes serous and mixed lineage endometrial tumors from five (3 African Americans, 1 Hispanic/Latino, 1 Caucasian) cases. In addition to bulk whole exome sequencing, we utilized single cell whole genome sequencing to assess global copy number heterogeneity. OCT-embedded frozen tumor sections were dissociated to collect nuclei, which were subjected to single nuclei sequencing using the 10x ChromiumTM single cell copy number variation (scCNV) assay targeting 500 cells per sample. Single cell libraries were quality assessed and sequenced using the Illumina NovaSeq6000 system. Data were processed using the 10X Genomics CellRanger pipeline for assessment of copy number heterogeneity. Results: We generated scCNV data on a total of 1,546 cells across five tumors. Hierarchical clustering and visual inspection of scCNV data reveals obvious somatic copy number tumor cell heterogeneity in all samples, including single and mixed histology tumors. Heterogeneity was mostly distinguished by whole chromosome or chromosome arm level gains or losses. Clonal focal amplifications were detected at 5p, 8p, 8q, and 17q encompassing known oncogenes. As we are able to identify clustered diploid populations of normal cells, we are using these data to perform segregation analysis for CGH analysis and the identification of somatic mutations in clonal populations of cells. These data are being compared to bulk exome sequencing data to determine the power of scCNV for detecting clonal populations of tumor cells. Conclusions: This project used high resolution single cell sequencing in five endometrial cancers with varying histologies. scCNV analysis provided clear evidence of heterogeneity in all tumors that were assessed in our study. This single cell whole genome data is being further analyzed for the presence of focal events, breakpoints and mutations that further stratify clonal tumor cell components in these cases. We plan to further expand this cohort to establish additional evidence for heterogeneity in endometrial cancer. Citation Format: Enrique I. Velazquez Villarreal, Lee D. Gibbs, Dana Mahinbakht, Diane M. Da Silva, Lynda D. Roman, David W. Craig, John D. Carpten. Identifying genomic heterogeneity at single-cell resolution in endometrial cancer [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 2199.

Background: While genomic alterations are central players in tumor progression, proteins are the targets for precision therapy. The degree by which “actionable” genomic alterations translate into activated/altered proteins and pathway is still under investigation. Using a multi-OMIC approach from the SideOut 2 metastatic breast cancer (MBC) trial, this study explored the concordance between selected “actionable” genomic alterations and protein expression/activation. Methods: Snap frozen biopsies from 29 MBC patients enrolled in a prospective phase II trial were used for this analysis. Exome WES and RNASeq data was processed using an in-house developed pipeline and identified amplification of CCND1 (6/29), FGFR1 (4/29), and FGF 3, 4, 5, and 19 (4/29) as some of most frequent “actionable” genomic alterations in our MBC cohort. Signaling analysis of the 29 cases was performed using Reverse Phase Protein Microarray coupled with Laser Capture Microdissection. Protein expression/phosphorylation was measured in a continuous scale and classified based on quartile distribution. Concordance between CCND1 amplification and Cyclin D1 expression, along with the activation of FOXM1 T600 and Rb S780, was explored. Amplification of the FGFR1 locus or its ligands was correlated with the level of activation/phosphorylation of FGFR1 Y653/654. Results: While Cyclin D1 protein expression was greater than the population mean for 4/6 (67%) patients with CCND1 amplification, only 2/6 (33%) patients with CCND1 amplification had Cyclin D1 level within the top quartile of the population (n=29). FOXM1 T600 activation was independent from CCND1 amplification, with high levels of FOXM1 T600 predominantly in the CCND1 wild-type population. Only 1/6 (17%) patients with CCND1 amplification had FOXM1 T600 level similar to the top quartile of the population while a second patient was above the population median. Activation of Rb S780 was above the population median, but below the top quartile, in 2/6 (33%) CCND1 amplified patients. Similarly, none of the patients with activation of FGFR Y653/654 equal to the top quartile harbored an FGFR1 amplification. Only 1/4 (25%) patients carrying an FGFR1 amplification had an activation of FGFR Y653/654 above the population median. Similarly, 1/4 (25%) patients with FGF ligand amplification showed FGFR Y653/654 level within the top quartile while three patients had FGFR Y653/654 activation below the population median. No significant results were found between proteomic (below/above the median) and genomic characteristics by Fisher test (p>0.05). Conclusion: Molecular genotyping of “actionable” cancer targets alone may be insufficient in predicting whether the actual drug target protein is expressed and/or activated in any given patient's tumor. Although these results need further validation, the combination of genomic and proteomic data may represent a more informative approach for identifying real molecular drivers of individual lesions as well as “actionable” protein/phosphoprotein targets in the absence of genomic events. Multi-OMIC approaches may lead to more effective stratification in precision medicine trials. Citation Format: Pierobon M, Wong S, Reeded A, Anthony S, Robert N, Northfelt DW, Jahanzeb M, Vocila L, Wulfkuhle J, Dunetz B, Aldrich J, Byron S, Craig D, Liotta L, Carpten J, Petricoin EF. A multi-OMIC analysis to explore the impact of “actionable” genomic alterations on protein pathway activation: Clinical implication for precision medicine in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-07-09.

Endometrial cancer is the fourth most common gynecologic malignancy in the US. Tumor- associated genetic signatures are known to be associated with poorer prognosis of patients with endometrial cancer. In general, frequent gene alterations are enrichments of p53 and KRAS, PTEN, PIK3CA and PI3K/AKT mutations with variable CNV. Considerable evidence for intratumor heterogeneity indicate that bulk genomic sequencing approaches may be insufficient since endometrial cancer is characterized by extensive tumor heterogeneity. Here, to get new insight about endometrial cancer heterogeneity, we applied single cell sequencing since it has the potential to improve our understanding of this genetic feature by providing clonotype and variant information in high resolution. We examined cancer heterogeneity using single cell DNA sequencing Copy Number Variation (sc-DNAseq-CNV) analysis and clonotype detection in three tumors from patients with endometrial cancer. The technology used for processing single cell was 10x ChromiumTM Technology that provides detection of 100 Kb CNV events, calling clonotypes down to 10 of 1000 cell inputs. By processing these samples resulted in the sequencing of around 800 cells. Genome-wide ploidy analysis of the tumor cells showed variable median ploidies per sample. The regional copy number was estimated by processing our data in 20 Kb cases of reads. Multiple sub-clones were identified per sample number one where four clusters of sub-clones characterized cancer heterogeneity. Copy number changes on entire chromosome arms and mutations at variant detection level were detected since the resolution provided by single cell technology applied. Among the variant detection we identified previously reported mutations in POLE, POLE2, TP53, FGFR2, ARID1A, CTNNBI, PIK3CA, PIK3RI, KRAS and SWI/SNF in specific sub clones. Our study addresses the predominant challenge to determine tumor heterogeneity by performing better approaches to detect genomic differences and identifying molecular signatures among women with endometrial cancer. Better understanding of tumor heterogeneity may benefit patients diagnosed with endometrial cancer, or patients with specific molecular characteristics linked to endometrial cancer. Citation Format: Enrique I. Velazquez Villarreal, John D. Carpten, David W. Craig. Understanding endometrial cancer heterogeneity at single-cell resolution [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 2507.

Background: The identification of organ-specific targetable signatures may help design more effective treatment for patients with metastatic breast cancer (MBC). We took a multi-OMIC approach to assess whether the AKT-mTOR pathway is globally activated during metastatic progression or whether it represents an organ-specific target. Methods: Snap frozen biopsies from 25 MBC patients enrolled in a prospective phase II trial were used. Sites of metastasis were classified as liver (n=8) and others (n=17), the latter including cutaneous, lung, lymph nodes, and intra-abdominal lesions. Signaling analysis of the 25 cases was performed using Reverse Phase Protein Microarray (RPPA) coupled with Laser Capture Microdissection. Activation of the AKT-mTOR pathway was quantified as phosphorylation of AKT (S473) and the mTOR target p70S6 (T389). Matched exome (WES) and RNASeq data were available for 17 of 25 patients, five with liver metastases. Sequencing data was processed using an in-house developed pipeline to identify somatic events including coding mutations, copy number alterations, gene fusions, and differential expression. Activation of the AKT-mTOR pathway and sequencing data were compared between hepatic and non-hepatic lesions using an integrated RPPA and genomic approach. Results: Among liver metastases, AKT was activated in 4 of the 8 (50.0%) patients, while 6 of the 8 cases (75.0%) showed activation of p70S6. Sequencing data revealed mutation of PIK3CA in 4 of the 5 liver metastases (80.0%). Three of the PIK3CA mutated specimens with catalytic domain mutations (codons 1023 and 147) demonstrated co-activation of AKT and p70S6, while the fourth case, containing a helical domain mutation (E542K), had activation of p70S6 only. The PIK3CA wild-type liver metastasis demonstrated low activation of AKT and p70S6. For non-hepatic metastases AKT was activated in 2 of the 17 cases (11.8%) and p70S6 in 5 of the 17 patients (29.4%). Discussion: Although these results need further validation, activation of the AKT-mTOR pathway appears to be a hepatic specific signature in MBC and could be used for the selection of targeted agents for hepatic lesions. Citation Format: Pierobon M, Wong S, Reeder A, Anthony SP, Robert NJ, Northfelt DW, Jahanzeb M, Vocila L, Wulfkuhle J, Dunetz B, Aldrich J, Byron S, Craig D, Liotta L, Petricoin EF, Carpten J. The AKT-mTOR pathway as a potential organ-specific drug target signature of hepatic metastases from breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-05-21.

Renal cell carcinoma (RCC) is one of the most lethal urological malignancies that would benefit from understanding cancer heterogeneity to identify molecular signatures providing potential innovative therapeutic targets. Renal cell carcinoma is characterized by extensive cancer heterogeneity. Single cell sequencing has the potential to improve our understanding of cancer heterogeneity by providing clonotype detection. We examined cancer heterogeneity using single-cell copy-number analysis and clonotype detection in four renal cancer tumors. The technology used for processing single cell was 10x ChromiumTM Technology that provides detection of 100 Kb CNV events, calling clonotypes down to 10 of 1000 cell inputs. By processing each of the four samples it resulted 469 total cells from sample one where 268 were tumor and 171 were normal; sample two resulted with 888 cells where 51 were tumor and 820 were normal; sample three resulted with 673 total cells where 167 were tumor and 485 normal; finally, sample four resulted with 1298 cells where 511 were tumor and 758 normal. Genome-wide ploidy analysis of the four tumor cells showed variable median ploidies. The regional copy number was estimated by processing our data in 20 Kb cases of reads. Multiple sub-clones were identified in sample number one where four clusters of sub-clones characterized cancer heterogeneity. Fast maximum-likelihood (ML) genetic clustering and Bayesian Information Criterion (BIC) were implemented on sample one to select the optimal clustering solution and provide a better insight of sub-clonal evolution. These sub-clones reported events such as copy number changes on entire chromosomes arms. The single cell resolution provided the ability of variant detection where we identified VHL gene mutations that are consistent with recent reports that describe its role as a molecular signature of disease outcome and drug efficacy in RCC. In conclusion, our findings describe sub-clones with large-scale events that provide new insights in understanding cancer heterogeneity in RCC. Citation Format: Enrique I. Velazquez Villarreal, John D. Carpten, David W. Craig. Understanding cancer heterogeneity in relation to minor sub-clones at single cell profiling level in renal cell carcinoma [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 2530.

Lung cancer remains the leading cause of cancer deaths in the US and throughout the world. Never-smokers with lung cancer constitute an understudied subset of these patients, though recent estimates show that ∼10% of men and women with lung cancer in the US are never-smokers. Independently, lung cancer in never-smokers ranks among the ten most common causes of cancer mortality, and thus the causes, driver pathways, and potential therapeutics must be investigated for this clinically relevant subpopulation. We hypothesize that novel mutations and pathways identified by whole genome sequencing (WGS) and whole transcriptome sequencing (WTS) drive tumorigenesis in adenocarcinomas of never-smoker patients, and represent potential therapeutic targets. We have completed WGS and WTS on two lung adenocarcinomas from female, never-smokers, one early-stage and one advanced-stage (metastatic), and one female smoker patient with early-stage lung adenocarcinoma. Approximately 100 short nucleotide variants (SNV) causing non-synonymous DNA sequence changes were discerned from the early- and advanced-stage adenocarcinomas from never-smokers. Of interest, these never-smoker patients lacked alterations in common genes associated with lung cancer such as EGFR, KRAS, and EML/ALK translocations, making them ideal cases for the discovery of new mutations that may drive lung adenocarcinomas in never-smokers. In comparison, the adenocarcinoma from a smoker patient contained 78 SNVs, including a well-characterized KRAS mutation. Mutations in MAGEC1, a tumor marker in melanoma and multiple myeloma, were observed in common between the early-stage, never-smoker tumor and the smoker tumor. The mutations observed in the never-smoker cases included genes suspected to play a role in lung carcinogenesis. The early-stage, never-smoker patient contained a mutation in PIK3C3 and DOCK10, known to play a role in cancer cell migration, and CSNK1E, a casein kinase involved Wnt signaling and in beta catenin-induced cancer cell proliferation. The late-stage never-smoker patient demonstrated a p53 mutation, a mutation in the tumor suppressor LATS2, and a mutation in the DNA damage checkpoint gene, ATM. The mutations discovered in known tumor suppressor genes tended to be in the late-stage, never-smoke patient. Ingenuity Pathway Analysis implicated G-protein coupled receptor signaling for the early-stage never-smoker, Hif1α signaling for the smoker, and Sonic Hedgehog Signaling for the late-stage, never-smoker in both WGS and WTS. Currently, we are validating the identified mutations discovered by WGS using Sanger sequencing and surveying their frequency in ∼30 and ∼60 additional cases of lung adenocarcinoma from never-smokers and clinically matched smokers, respectively. Validation of these mutations and pathways will lead to a better understanding of tumorigenesis and tumor progression in never-smokers and identify nodes for therapeutic vulnerability.