Intratumoral Genetic Heterogeneity Research Articles

Unravelling Heterogeneity of Stem and Progenitor Cells in Myeloid Neoplasms Through Single Cell Multi-omics

Intratumoural heterogeneity (ITH) underlies many of the challenges we face in cancer medicine, including therapy-resistance, disease progression/evolution and relapse after seemingly effective therapy. Distinct tumour cell subpopulations selectively evade therapy and drive disease-progression and technologies that reveal key aspects of ITH are therefore critical for the application of precision cancer medicine. Although bulk genomic analysis has without question provided many insights into genetic ITH, this approach faces a number of fundamental limitations: ITH in cancer occurs at many levels, not restricted to genetics (mutations) but also other factors, such as presence of cancer stem cells in some tumours. Furthermore, bulk genomic analysis reveals patterns of somatic mutations, but not their molecular consequences within distinct (and therapy-resistant) cancer subclones. Whilst many of the scientific questions relating to ITH have remained the same over many decades, our ability to address these questions has advanced dramatically not least because of advances in technology. Ultimately, as the unit of evolution and clonal selection by therapy in cancer is the cell, techniques that resolve heterogeneity at the single-cell level are ideally placed to unravel ITH and provide entirely new insights into cancer biology, with enormous potential to accelerate the development of new approaches to improve outcomes for patients. However, the lack of coverage across key mutation hotspots when studying cancers using single-cell RNA-sequencing techniques has precluded the correlation of genetic and transcriptional readouts from the same single cell, limiting their application to the study of tumors. To overcome such limitation, we developed TARGET-seq, a single cell multi-omic method for the high-sensitivity detection of mutations within single cells in parallel with whole transcriptome analysis. TARGET-seq achieved extremely low allelic dropout rates, allowing resolution of clonal hierarchies with over 98% accuracy, while obtaining unbiased high quality transcriptomes from the same single cell. We have applied TARGET-seq to the study of over ten thousand haematopoietic stem and progenitor cells (HSPCs) from JAK2-mutant myeloproliferative neoplasms. This analysis revealed a high degree of genetic heterogeneity, identifying both linear and branching patterns of clonal evolution. At the transcriptome level different genetic subclones showed distinct transcriptional signatures, indicating that each of them was molecularly distinct. Wild-type cells from MPN patients also showed disrupted gene expression as compared to cells from normal donors, upregulating molecular pathways associated with inflammation (TNFα, TGFβ and IFN signalling). This suggests cell-extrinsic effects disrupting gene expression in non-mutant cells, which has been shown to have prognostic significance and might underlie therapy response. Moreover, TARGET-seq analysis allowed us to identify putative biomarkers of JAK2V617F mutant cells, including novel therapeutic targets to selectively eradicate JAK2-mutant cells and importantly, potential candidates for antibody-based immunotherapy. Analysis of samples from MPN patients undergoing disease transformation to Acute Myeloid Leukemia (sAML) revealed striking patterns of clonal evolution in different immunophenotypically-defined cell types. We identified pre-leukemic and leukemic subclones emerging from hematopoietic stem cells rather than more mature progenitors, in contrast to evolution patterns in de novo AML, which might indicate different cancer stem cell reservoirs. In summary, TARGET-seq allowed us to identify distinct and biologically relevant molecular signatures of different genetic subclones of HSPCs in myeloproliferative neoplasms. TARGET-seq could also be broadly applied to the study of other types of tumours, providing a powerful tool for biomarker and therapeutic target discovery for precision medicine. Disclosures Mead: Bristol Myers-Squibb: Consultancy; Pfizer: Consultancy; Novartis: Consultancy, Honoraria, Other: Travel/accommodation expenses, Research Funding, Speakers Bureau; CTI: Honoraria, Research Funding; Celgene: Consultancy, Research Funding.

Evolution of Clinically Relevant Subclones during Chemotherapy Treatment of ALL As Determined By Single-Cell DNA and RNA Sequencing

Acute lymphoblastic leukemia (ALL), which is the most common cancer in children, shows extensive genetic intra-tumoral heterogeneity. This heterogeneity might be the underlying reason for an incomplete response to treatment and for the development of relapse. In order to envision the clinical implementation of a refined risk-category strategy based on ALL subclonal composition, it is essential to first generate a reference single-cell map and accumulate evidence on how the subclonal composition affects the response to treatment. For that, we performed large-scale and integrative single-cell genome and transcriptome profiling of pediatric samples at diagnosis, during drug treatment and in case of relapse. We used the 10x Genomics platform for single-cell RNA-sequencing analysis (around 4000 cells per sample) and the Tapestri Platform (Mission Bio) for targeted single-cell DNA-sequencing (around 5000 cells per sample) of the most mutated genomic regions in ALL. For the later, we developed a custom panel that covers 305 ALL mutational hotspots across 110 genes. We have determined a reference single-cell map of the cellular (based on the gene expression profile) and the clonal composition (based on the co-occurrence of mutations at each individual cell) for pediatric ALL at diagnosis (8 T-ALL and 10 B-ALL patients). We have also reconstructed the tumor phylogeny highlighting the order of mutational acquisition and the most likely pattern of evolution. Moreover, we have studied how T-ALL evolves during drug treatment at single-cell resolution in 4 patients, unraveling which are the most sensitive clones to the therapy, which are the most resistant ones and when relapse clones originated. Single-cell RNA-sequencing also provided information on how normal hematopoiesis recovers during chemotherapy treatment. The results show that ALL is typically composed by a major clone and 5-10 smaller clones that have different sensitivities to the therapy. We have been able to detect minor clones (<1% of the cells) at diagnosis that are clinically relevant. These very rare clones are either not responding to the therapy (present at minimal residual disease) or form the relapsed leukemia. These findings could have clinical implications for improved risk-stratification methods based on individualized patient's molecular profiles. Disclosures Maertens: Gilead Sciences: Other: Grants, personal fees and non-financial support; Cidara: Other: Personal fees and non-financial support; Amplyx: Other: Personal fees and non-financial support; F2G: Other: Personal fees and non-financial support; Merck: Other: Personal fees and non-financial support; Pfizer: Other: Grant and personal fees; Astellas Pharma: Other: Personal fees and non-financial support.

Non-Genetic Intra-Tumor Heterogeneity Is a Major Predictor of Phenotypic Heterogeneity and Ongoing Evolutionary Dynamics in Lung Tumors

SUMMARYImpacts of genetic and non-genetic intra-tumor heterogeneity (ITH) on tumor phenotypes and evolvability remain debated. We analyze ITH in lung squamous cell carcinoma at the levels of genome, transcriptome, and tumor-immune interactions and histopathological characteristics by multi-region bulk and single-cell sequencing. Genomic heterogeneity alone is a weak indicator of intra-tumor non-genetic heterogeneity at immune and transcriptomic levels that impact multiple cancer-related pathways, including those related to proliferation and inflammation, which in turn contribute to intra-tumor regional differences in histopathology and subtype classification. Tumor subclones have substantial differences in proliferation score, suggestive of non-neutral clonal dynamics. Proliferation and other cancer-related pathways also show intra-tumor regional differences, sometimes even within the same subclones. Neo-epitope burden negatively correlates with immune infiltration, indicating immune-mediated purifying selection on somatic mutations. Taken together, our observations suggest that non-genetic heterogeneity is a major determinant of heterogeneity in histopathological characteristics and impacts evolutionary dynamics in lung cancer.

The Role of Tumor Microenvironment in Genomic Instability of Malignant Tumors.

Genomic instability is an essential feature of cancer cells. The somatic mutation theory suggests that along with inherited ones, the changes in DNA caused by environmental factors may cause cancer. Although approximately 50–60 mutations per tumor are observed in established cancer tissue, it is known that not all of these mutations occur at the beginning of carcinogenesis but also occur later in the disease progression. The high frequency of somatic mutations referring to genomic instability contributes to the intratumoral genetic heterogeneity and treatment resistance. The contribution of the tumor microenvironment to the mutations observed following the acquirement of essential malignant characteristics of a cancer cell is one of the topics that have been extensively investigated in recent years. The frequency of mutations in hematologic tumors is generally less than solid tumors. Although it is a hematologic tumor, multiple myeloma is more similar to solid tumors in terms of the high number of chromosomal abnormalities and genetic heterogeneity. In multiple myeloma, bone marrow microenvironment also plays a role in genomic instability that occurs in the very early stages of the disease. In this review, we will briefly summarize the role of the tumor microenvironment and bone marrow microenvironment in the genomic instability seen in solid tumors and multiple myeloma.

EcSeg: Semantic Segmentation of Metaphase Images Containing Extrachromosomal DNA.

SummaryOncogene amplification is one of the most common drivers of genetic events in cancer, potently promoting tumor development, growth, and progression. The recent discovery that oncogene amplification commonly occurs on extrachromosomal DNA, driving intratumoral genetic heterogeneity and high copy number owing to its non-chromosomal mechanism of inheritance, raises important questions about how the subnuclear location of amplified oncogenes mediates tumor pathogenesis. Next-generation sequencing is powerful but does not provide spatial resolution for amplified oncogenes, and new approaches are needed for accurately quantifying oncogenes located on ecDNA. Here, we introduce ecSeg, an image analysis tool that integrates conventional microscopy with deep neural networks to accurately resolve ecDNA and oncogene amplification at the single cell level.

CUTseq is a versatile method for preparing multiplexed DNA sequencing libraries from low-input samples

Current multiplexing strategies for massively parallel sequencing of genomic DNA mainly rely on library indexing in the final steps of library preparation. This procedure is costly and time-consuming, because a library must be generated separately for each sample. Furthermore, library preparation is challenging in the case of fixed samples, such as DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissues. Here we describe CUTseq, a method that uses restriction enzymes and in vitro transcription to barcode and amplify genomic DNA prior to library construction. We thoroughly assess the sensitivity and reproducibility of CUTseq in both cell lines and FFPE samples, and demonstrate an application of CUTseq for multi-region DNA copy number profiling within single FFPE tumor sections, to assess intratumor genetic heterogeneity at high spatial resolution. In conclusion, CUTseq is a versatile and cost-effective method for library preparation for reduced representation genome sequencing, which can find numerous applications in research and diagnostics.

Mutant-allele tumor heterogeneity in malignant glioma effectively predicts neoplastic recurrence.

Intra-tumor heterogeneity (ITH) is one of the most important causes of therapy resistance, which eventually leads to the poor outcomes observed in patients with glioma. Mutant-allele tumor heterogeneity (MATH) values are based on whole-exon sequencing and precisely reflect genetic ITH. However, the significance of MATH values in predicting glioma recurrence remains unclear. Information of patients with glioma was obtained from The Cancer Genome Atlas database. The present study calculated the MATH value for each patient, analyzed the distributions of MATH values in different subtypes and investigated the rates of clinical recurrence in patients with different MATH values. Gene enrichment and Cox regression analyses were performed to determine which factors influenced recurrence. A nomogram table was established to predict 1-, 2- and 5-year recurrence probabilities. MATH values were increased in patients with glioma with the wild-type isocitrate dehydrogenase (NADP(+)) (IDH)1/2 (IDH-wt) gene (P=0.001) and glioblastoma (GBM; P=0.001). MATH values were negatively associated with the 2- and 5-year recurrence-free survival (RFS) rates in patients with glioma, particularly in the IDH1/2-wt and GBM cohorts (P=0.001 and P=0.017, respectively). Furthermore, glioma cases with different MATH levels had distinct patterns of gene mutation frequencies and gene expression enrichment. Finally, a nomogram table that contained MATH values could be used to accurately predict the probabilities of the 1-, 2- and 5-year RFS of patients with glioma. In conclusion, the MATH value of a patient may be an independent predictor that influences glioma recurrence. The nomogram model presented in the current study was an appropriate method to predict 1-, 2- and 5-year RFS probabilities in patients with glioma.

Clonal evolution of esophageal squamous cell carcinoma from normal mucosa to primary tumor and metastases.

The clonal evolution which drives esophageal squamous cell carcinoma (ESCC) from initiation in normal cell to primary carcinoma and metastases is poorly understood. In this study, multi-region whole-exome sequencing (WES) (284X) and whole-genome single nucleotide polymorphism genotyping were performed on a total of 109 samples of ESCC from 10 patients. This included 42 apparently normal samples of esophageal mucosa at increasing distances from the upper or lower boundaries of the primary tumor to the surgical margins of resection, 43 spatially separated tissue samples within primary tumor and 24 regional lymph node metastases. Phylogenetic analysis was performed to reconstruct ancestor-descendant relationships of clones and the clonal composition of multi-region samples. Mutations of cancer-related genes were validated by deep targeted sequencing (1,168X). Both inter- and intra-tumoral genetic heterogeneity were obvious across multi-region samples among ESCC patients. Clones varying in number from one to seven were discovered within each regional tumor or metastatic sample. Phylogenetic analysis demonstrated complex clonal evolution patterns. Regional lymph node metastases had characteristics of early initiation and polyclonal spreading, and could be derived from carcinoma in situ (CIS) directly. TP53 was the only gene harboring non-silent mutations identified across all multi-region tumor samples of all ten patients. Mutations of TP53 were also found in histologically normal mucosa in sites away from primary tumor.

The Effects of Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer-The Impact in Intratumoral Heterogeneity.

Purpose: Intratumoral genetic heterogeneity (ITGH) is a common feature of solid tumors. However, little is known about the effect of neoadjuvant chemoradiation (nCRT) in ITGH of rectal tumors that exhibit poor response to nCRT. Here, we examined the impact of nCRT in the mutational profile and ITGH of rectal tumors and its adjacent irradiated normal mucosa in the setting of incomplete response to nCRT.Methods and Materials: To evaluate ITGH in rectal tumors, we analyzed whole-exome sequencing (WES) data from 79 tumors obtained from The Cancer Genome Atlas (TCGA). We also compared matched peripheral blood cells, irradiated normal rectal mucosa and pre and post-treatment tumor samples (PRE-T and POS-T) from one individual to examine the iatrogenic effects of nCRT. Finally, we performed WES of 7 PRE-T/POST-T matched samples to examine how nCRT affects ITGH. ITGH was assessed by quantifying subclonal mutations within individual tumors using the Mutant-Allele Tumor Heterogeneity score (MATH score).Results: Rectal tumors exhibit remarkable ITGH that is ultimately associated with disease stage (MATH score stage I/II 35.54 vs. stage III/IV 44.39, p = 0.047) and lymph node metastasis (MATH score N0 35.87 vs. N+ 45.79, p = 0.026). We also showed that nCRT does not seem to introduce detectable somatic mutations in the irradiated mucosa. Comparison of PRE-T and POST-T matched samples revealed a significant increase in ITGH in 5 out 7 patients and MATH scores were significantly higher after nCRT (median 41.7 vs. 28.8, p = 0.04). Finally, we were able to identify a subset of “enriched mutations” with significant changes in MAFs between PRE-T and POST-T samples. These “enriched mutations” were significantly more frequent in POST-T compared to PRE-T samples (92.9% vs. 7.1% p < 0.00001) and include mutations in genes associated with genetic instability and drug resistance in colorectal cancer, indicating the expansion of tumor cell subpopulations more prone to resist to nCRT.Conclusions: nCRT increases ITGH and may result in the expansion of resistant tumor cell populations in residual tumors. The risk of introducing relevant somatic mutations in the adjacent mucosa is minimal but non-responsive tumors may have potentially worse biological behavior when compared to their untreated counterparts. This was an exploratory study, and due to the limited number of samples analyzed, our results need to be validated in larger cohorts.

Rectal cancer sub-clones respond differentially to neoadjuvant therapy

Treatment of locally advanced rectal cancer includes chemotherapy, radiation, and surgery but patient responses to neoadjuvant treatment are variable. We have shown that rectal tumors are comprised of multiple genetically distinct sub-clones. Unique sub-clones within tumors may harbor mutations which contribute to inter-patient variation in response to neoadjuvant chemoradiotherapy (nCRT). Analysis of the influence of nCRT on the extent and nature of intra-tumoral genetic heterogeneity in rectal cancer may provide insights into mechanisms of resistance.Locally advanced rectal cancer patients underwent pre-treatment biopsies. At the time of surgery, tissue from the treated tumor was obtained and analyzed. Pre- and post-treatment specimens were subjected to whole exome and confirmatory deep sequencing for somatic mutations. Copy number variation was assessed using OncoScan SNP arrays. Genomic data were analyzed using PyClone to identify sub-clonal tumor population following nCRT. Alterations that persisted or were enriched in the post-treatment tumor specimen following nCRT were defined for each patient.Thirty-two samples were obtained from ten patients. PyClone identified 2 to 10 genetic sub-clones per tumor. Substantial changes in the proportions of individual sub-clones in pre- versus post-treatment tumor material were found in all patients. Resistant sub-clones recurrently contained mutations in TP53, APC, ABCA13, MUC16, and THSD4. Recurrent copy number variation was observed across multiple chromosome regions after nCRT. Pathway analysis including variant alleles and copy number changes associated with resistant sub-clones revealed significantly altered pathways, especially those linked to the APC and TP53 genes, which were the two most frequently mutated genes.Intra-tumoral heterogeneity is evident in pre-treatment rectal cancer. Following treatment, sub-clonal populations are selectively modified and enrichment of a subset of pre-treatment sub-clones is seen. Further studies are needed to define recurrent alterations at diagnosis that may contribute to resistance to nCRT.

Genetic hallmarks of recurrent/metastatic adenoid cystic carcinoma.

BACKGROUNDAdenoid cystic carcinoma (ACC) is a rare malignancy arising in salivary glands and other sites, characterized by high rates of relapse and distant spread. Recurrent/metastatic (R/M) ACCs are generally incurable, due to a lack of active systemic therapies. To improve outcomes, deeper understanding of genetic alterations and vulnerabilities in R/M tumors is needed.METHODSAn integrated genomic analysis of 1,045 ACCs (177 primary, 868 R/M) was performed to identify alterations associated with advanced and metastatic tumors. Intratumoral genetic heterogeneity, germline mutations, and therapeutic actionability were assessed.RESULTSCompared with primary tumors, R/M tumors were enriched for alterations in key Notch (NOTCH1, 26.3% vs. 8.5%; NOTCH2, 4.6% vs. 2.3%; NOTCH3, 5.7% vs. 2.3%; NOTCH4, 3.6% vs. 0.6%) and chromatin-remodeling (KDM6A, 15.2% vs. 3.4%; KMT2C/MLL3, 14.3% vs. 4.0%; ARID1B, 14.1% vs. 4.0%) genes. TERT promoter mutations (13.1% of R/M cases) were mutually exclusive with both NOTCH1 mutations (q = 3.3 × 10-4) and MYB/MYBL1 fusions (q = 5.6 × 10-3), suggesting discrete, alternative mechanisms of tumorigenesis. This network of alterations defined 4 distinct ACC subgroups: MYB+NOTCH1+, MYB+/other, MYBWTNOTCH1+, and MYBWTTERT+. Despite low mutational load, we identified numerous samples with marked intratumoral genetic heterogeneity, including branching evolution across multiregion sequencing.CONCLUSIONThese observations collectively redefine the molecular underpinnings of ACC progression and identify further targets for precision therapies.FUNDINGAdenoid Cystic Carcinoma Research Foundation, Pershing Square Sohn Cancer Research grant, the PaineWebber Chair, Stand Up 2 Cancer, NIH R01 CA205426, the STARR Cancer Consortium, NCI R35 CA232097, the Frederick Adler Chair, Cycle for Survival, the Jayme Flowers Fund, The Sebastian Nativo Fund, NIH K08 DE024774 and R01 DE027738, and MSKCC through NIH/NCI Cancer Center Support Grant (P30 CA008748).

Glutathione transferase genotypes may serve as determinants of risk and prognosis in renal cell carcinoma

Renal cell carcinoma (RCC) represents a group of histologically similar neoplasms with significant intratumor and intertumor genetic heterogeneity. Recognized risk factors for RCC development include smoking, hypertension, obesity, as well as von Hippel-Lindau (VHL) disease. Inactivation of VHL, deregulated nuclear factor (erythroid-derived 2)-like 2 (Nrf2) pathway, and altered redox homeostasis, together with changes in glutathione transferase (GST) profile, are considered as important contributing factors in RCC development and progression. Although the available results of both gene-gene and gene-environment analysis are quite heterogeneous, they clearly indicate that certain GST genotypes may play a role as risk modifiers, either individually or in combination with other Phase I or Phase II gene polymorphisms, as well as in subjects exposed to relevant substrates. Seemingly, GST genotyping could identify individuals with impaired detoxification in renal parenchyma that are at higher risk of developing RCC. In addition to well established roles of GSTs in conjugation and biotransformation of xenobiotics, GSTs have emerged as significant regulators of pathways determining cell proliferation and survival. Indeed, there are evidence in favor of GST significance, not only in terms of risk for RCC development, but also with respect to progression and prognosis. So far, GSTM1-active genotype was confirmed to be an independent predictor of higher risk of overall mortality. Therefore, it is reasonable to assume that certain GST variants may assist in individual RCC risk assessment, as well as postoperative prognosis. Even more, GST profiling might contribute to development of personalized targeted therapy in RCC patients.

An analysis of genetic heterogeneity in untreated cancers.

Genetic intratumoural heterogeneity is a natural consequence of imperfect DNA replication. Any two randomly selected cells, whether normal or cancerous, are therefore genetically different. Here, we review the different forms of genetic heterogeneity in cancer and re-analyse the extent of genetic heterogeneity within seven types of untreated epithelial cancers, with particular regard to its clinical relevance. We find that the homogeneity of predicted functional mutations indriver genes is the rule rather than the exception. In primary tumours with multiple samples, 97% of driver-gene mutations in 38 patients were homogeneous. Moreover, among metastases from the same primary tumour, 100% of the driver mutations in 17 patients were homogeneous. With a single biopsy of a primary tumour in 14 patients, the likelihood of missing a functional driver-gene mutation that was present in all metastases was 2.6%. Furthermore, all functional driver-gene mutations detected in these 14 primary tumours were present among all their metastases. Finally, we found that individual metastatic lesions responded concordantly to targeted therapies in 91% of 44patients. These analyses indicate that the cells within the primary tumours that gave rise to metastases are genetically homogeneous with respect to functional driver-gene mutations, and we suggest that future efforts to develop combination therapies have the potential to be curative.

Spatial Distance Correlates With Genetic Distance in Diffuse Glioma.

Background: Treatment effectiveness and overall prognosis for glioma patients depend heavily on the genetic and epigenetic factors in each individual tumor. However, intra-tumoral genetic heterogeneity is known to exist and needs to be managed. Currently, evidence for genetic changes varying spatially within the tumor is qualitative, and quantitative data is lacking. We hypothesized that a greater genetic diversity or “genetic distance” would be observed for distinct tumor samples taken with larger physical distances between them.Methods: Stereotactic biopsies were obtained from untreated primary glioma patients as part of a clinical trial between 2011 and 2016, with at least one biopsy pair collected in each case. The physical (Euclidean) distance between biopsy sites was determined using coordinates from imaging studies. The tissue samples underwent whole exome DNA sequencing and epigenetic methylation profiling and genomic distances were defined in three separate ways derived from differences in number of genes, copy number variations (CNV), and methylation profiles.Results: Of the 31 patients recruited to the trial, 23 were included in DNA methylation analysis, for a total of 71 tissue samples (14 female, 9 male patients, age range 21–80). Samples from an 8 patient subset of the 23 evaluated patients were further included in whole exome and copy number variation analysis. Physical and genomic distances were found to be independently and positively correlated for each of the three genomic distance measures. The correlation coefficients were 0.63, 0.65, and 0.35, respectively for (a) gene level mutations, (b) copy number variation, and (c) methylation status. We also derived quantitative linear relationships between physical and genomic distances.Conclusion: Primary brain tumors are genetically heterogeneous, and the physical distance within a given glioma correlates to genomic distance using multiple orthogonal genomic assessments. These data should be helpful in the clinical diagnostic and therapeutic management of glioma, for example by: managing sampling error, and estimating genetic heterogeneity using simple imaging inputs.

Is high-risk cutaneous squamous cell carcinoma of the head and neck a suitable candidate for current targeted therapies?

ObjectiveCutaneous squamous cell carcinoma (cSCC) is the second most common malignancy, most frequently affecting the head and neck. Treatment often requires surgery and can have significant functional morbidity. Research into...

Abstract 3097: Investigating an aggressive molecular subtype of stage I lung adenocarcinoma: Evidences for the acquirement of stem-like and immune evasion phenotype

Abstract Lung cancer early diagnosis is effective in reducing the risk of metastatic disease and improve overall survival. However, a significant fraction of patients (~20%) with early stage disease (Stage I) experience tumor recurrence and metastatic disease. Recent advances in high-throughput genomic screening allowed an in-depth molecular profile analyses of lung cancer, with particular emphasis for the identification of prognostic gene expression signatures. Indeed, we recently described the existence of an aggressive lung adenocarcinoma (LUAD) molecular subtype (Stage I), namely C1-LUAD, with a peculiar expression and mutational profile more resembling advanced metastatic cancer. Using an integrative approach relying on computational biology and lung cancer experimental models, we now discovered that this C1-subtype is characterized by stem-like and immune evading phenotype. In particular, gene-set enrichment analysis (GSEA) revealed that ‘C1-LUAD’ tumors are enriched in stem cell (SC) expression signatures (q-value&amp;lt;0.05). Notably, the gene network characterizing the C1-LUAD subtype was downstream to known transcriptional modulators involved in SC biology. In line with this, we found several iPS/Stem and EMT biomarkers overexpressed in C1-LUAD and in a panel of C1-LUAD-like lung cancer cells. Furthermore, forced overexpression of HOXB7 gene, a biomarker of C1-LUAD and a member of the Antp homeobox family, promotes the expansion of lung sphere-forming cells and reprogramming into iPS cells. Lastly, we performed an analysis of the Immune Subtypes and ImmunoPhenoScore in C1-LUAD tumors coupled with tumor mutational burden (TMB) and intra-tumor genetic heterogeneity (ITH) profile, which revealed: i) a predominance of the tumor permissive ‘C1 wound healing' subtype (i.e. high Th2/TAMs, low CD8+Tc); ii) a reduction of the ‘C3 inflammatory' subtype; iii) an increased ITH; and iv) a reduction of neoantigen burden. These are hallmarks of cancer immunoediting process which ultimately favor tumor cell escape. In conclusion, we identified an aggressive subtype of LUAD characterized by a stem-like and immune evasion phenotype. C1-LUAD can be identified by qPCR analysis using a panel of 10 genes, previously validated in a large cohort of FFPE samples. Our findings can contribute to improve survival of lung cancer patients by anticipating diagnosis of aggressive Stage I tumors and may pave the way for developing more effective therapeutic strategies. Citation Format: Valentina Melocchi, Elisa Dama, Roberto Cuttano, Tommaso Colangelo, Paolo Graziano, Fabrizio Bianchi. Investigating an aggressive molecular subtype of stage I lung adenocarcinoma: Evidences for the acquirement of stem-like and immune evasion phenotype [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 3097.

Abstract 1601: Genetic and epigenetic intratumor heterogeneity of lung adenocarcinoma

Abstract Genomic studies have revealed remarkable intratumoral heterogeneity (ITH) in lung adenocarcinoma (LUAD) and increasing evidence suggests its impact in cancer treatment. However, to what extent epigenomic abnormalities and somatic copy number alterations (SCNAs) are involved in shaping genetic clones in lung tumors and are associated with clinical outcome is under-appreciated. Here we applied Infinium HumanMethylation450K BeadChips, Infinium Global Screening Arrays and ultra-deep (&amp;gt;500X) targeted sequencing of 35 LUAD driver genes to 369 samples (including 77 normal tissues) from 84 LUAD patients to investigate the genetic and epigenetic architecture of subclonal diversification. SCNAs were mostly clonal events. For patients with more than three tumor regions assayed, 66% SCNAs were located on the trunk of the evolutionary trees. Similar evolutionary trajectories were inferred from SCNAs and DNA methylation. The driver genes’ sequencing depth allowed to identify subclonality even in TP53, EGFR, and BRAF mutations, which were largely reported as clonal events in previous studies. Elevated copy number ITH was associated with higher risk of death, while no significant association was found between clinical outcome and DNA methylation ITH or heterogeneous CpG island methylator phenotype (CIMP), in contrast with the observed prognostic capability of DNA methylation ITH in hematological malignancies. These findings expand our understanding of the coevolution of genetic and epigenetic aberrations in tumorigenesis, the subclonal complexity for therapeutic targets and the implication of ITH in cancer prognosis. Citation Format: Wei Zhao, Xing Hua, Tongwu Zhang, Dario Consonni, Angela Cecilia Pesatori, Jianxin Shi, Maria Teresa Landi. Genetic and epigenetic intratumor heterogeneity of lung adenocarcinoma [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 1601.

Abstract 2725: The single-cell atlas of driver mutations in acute myeloid leukemia

Abstract Assessment of intratumor genetic heterogeneity by next-generation sequencing (NGS) is confounded by tumor purity and zygosity of mutations. Furthermore, bulk NGS cannot visualize the cell-level co-occurrence or exclusivity among multiple mutations, causing the inaccurate inference of subclonal architecture. Here, we performed single cell DNA sequencing (scDNA seq) in 82 bone marrow samples from 70 patients with acute myeloid leukemia (AML) using a novel microfluidics-based platform covering 40 amplicons in 19 AML genes (Tapestri, Mission Bio). All samples were concurrently sequenced by the bulk NGS using 295 gene exome capture sequencing. Selected cases were also analyzed by SNP array (Illuminia Omni 2.5 array) to obtain allele-specific copy number data. In total, 319,406 cells (median 3,755 cells/sample) were genotyped with median allele drop-out rate of 8.7% (population frequency inferred from commonly heterozygous SNP loci). Each amplicon was covered at a median 24x/cell. The scDNA seq detected 230 of 238 (97%) bulk NGS-confirmed mutations. RUNX1 mutations were frequently detected as homozygous mutations and concurrent SNP array analysis detected copy number neutral loss-of-heterozygosity of RUNX1 in these cases. Additionally, in cases with homozygous FLT3-ITD mutations, SNP array detected allele-specific copy number gain of mutant loci, which likely resulted in homozygous calls. scDNA seq data unambiguously resolved the single-cell level co-occurrence of driver mutations in AML such as DNMT3A/FLT3-ITD/NPM1, SRSF2/IDH2, and ASXL1/RUNX1, confirming the cooperative function of these driver mutations. On the other hand, the data also revealed mutually exclusive relationships at cellular level between IDH1/IDH2, FLT3-ITD/TKD, NRAS/KRAS, NRAS/PTPN11, and SRSF2/EZH2 mutations, which supports the functional redundancy of these genes in leukemogenesis. Inference of phylogenetic trees using SCITE algorithm (Jahn et al. Genome Biology 2016) uncovered distinct patterns of clonal evolution in AML. The majority of the analyzed cases had a linear evolution pattern where the founder mutations linearly acquired sub-clonal mutations in a step-wise manner. We also detected convergent evolution in some cases where functionally similar driver mutations were acquired in parallel. DNMT3A, IDH1, IDH2 and U2AF1 mutations were frequently detected as trunk mutations, whereas FLT3, NRAS, and NPM1 mutations were usually detected as branch mutations. Analysis of longitudinal samples from 11 patients revealed the remodeling of clonal architecture at relapse. Patients who had 2 or more major subclones at baseline had significantly worse overall survival than those with one subclone (2-year OS 13 vs. 70 months, p = 0.0493). For the first time our data provides a comprehensive landscape of driver mutations and detailed clonal evolution history in AML at the single-cell level using high-throughput scDNA seq genotype information. Citation Format: Kiyomi Morita, Feng Wang, Katharina Jahn, Yuanqing Yan, Robert Durruthy-Durruthy, Anup Parikh, Jairo Matthews, Latasha Little, Curtis Gumbs, Jianhua Zhang, Xingzhi Song, Erika Thompson, Keyur Patel, Carlos Bueso-Ramos, Courtney DiNardo, Farhad Ravandi, Elias Jabbour, Michael Andreeff, Jorge Cortes, Marina Konopleva, Guillermo Garcia-Manero, Hagop Kantarjian, Dennis J. Eastburn, P Andrew Futreal, Niko Beerenwinkel, Koichi Takahashi. The single-cell atlas of driver mutations in acute myeloid leukemia [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 2725.

Abstract 5220: Transcription regulatory networks associated with luminal master regulator expression and breast cancer survival

Abstract The disparity in breast cancer burden of African Americans compared with European Americans is one of the most revealing instances in oncology associated with ethnicity. Recent studies demonstrated that there were highly intratumoral genetic heterogeneity and increased the frequency of basal subtypes among African Americans than European Americans. Because significant race-based disparities in breast cancer patients with hormone-receptor positive still persistent even after reflecting socio-economic status, there may be substantial roles playing by intrinsic biological factors contributing to the disparities. Transcriptional regulation governed by estrogen receptor plays critical roles in major changes in chromatin landscape that facilitate the assembly of other transcriptional complexes affecting mammary tumor initiation and proliferation. We investigated the estrogen receptor and its essential pioneer transcription factors how their expressions are associated with racial disparity with their prognostic significance. Co-expression analysis of estrogen receptor and its pioneer transcription factors suggest that ER-positive patients of women of European ancestry show much more favorable survival than women of African ancestry. Differential comparison of protein expression integrated with network-level gene expression analysis reveals significant differences in the predictive ability of the luminal master regulators based on race and survival. Moreover, we identified genes in the downstream of these master regulators that are highly correlated with race and survival. The comparative analysis of the predictive value of race-based cutoffs suggests that these master regulators of luminal differentiation have reduced transcriptional activity in the downstream regulatory network pathways in African ancestry. Functional characterization of the luminal master regulators and their downstream pathways may provide a better understanding of the intrinsic mechanisms that drive racial disparities in breast cancer survival. Citation Format: Jung S. Byun, Sandeep Singhal, Samson Park, Dae IK Yi, Ambar Caban, Nasreen Vohra, Eliseo J. Perez-Stable, Anna Napoles, Kevin L. Gardner. Transcription regulatory networks associated with luminal master regulator expression and breast cancer survival [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 5220.

Abstract 1180: Impact of the spatial analysis of tumor-associated lymphocytes and tumor-associated macrophages on recurrence at early stage of non-small cell lung carcinoma

Abstract Introduction. The interaction between malignant cells (MCs), stromal cells, tumor-associated lymphocytes (TILs), and tumor-associated macrophages (TAMs) is relevant for non-small cell lung carcinoma (NSCLC) progression. The spatial distribution of those cells may affect the prognosis and can be related to genetic intra-tumor heterogeneity (ITH). The aim of this study was to characterize the immunologic ITH and the spatial distribution of immune cells to MCs in primary NSCLC tumors at early stages using multiplex immunofluorescence (mIF) and image analysis approaches. Material and methods. We studied 33 surgically resected NSCLC cases (adenocarcinomas=23; squamous-cell carcinomas=10) with a history of recurrence in a follow-up of at least 60 months (recurrence, N=13; non-recurrence, N=15). Consecutive FFPE tissue sections were stained with two mIF panels (panel 1: cytokeratin (AE1/AE3), PD-L1, PD-1, CD3, CD8, and CD68; panel 2: AE1/AE3, CD3, CD8, granzyme-B, CD45RO, and FOXP3). Three intra-tumor regions (3mm2 each) per case were selected after gridding the whole tumor section. A total of 99 intratumor regions were scanned and analyzed using Vectra Multispectral-Microscope and InForm-software. From each intratumor region, TILs and TAMs densities, as well as the coefficient of variation, were evaluated. The median distance and the G-Cross area under the curve (AUC) for specific radial distances (10µm, 20µm, and 40µm) were obtained between TILs and TAMs phenotypes to MCs. Results. Recurrence was associated with higher MCs density and TAMs/TILs ratio, and lower TIL densities. A high ITH of cytotoxic T-cells (CTLs) PD-L1+ was associated with worse survival. The distance of TAMs PD-L1+ to MCs PD-L1 negative (60µm vs 25µm) or to MCs PD-L1 positive (25µm vs 13µm) was higher in the non-recurrence group than in recurrence group. Close TAMs PD-L1+ to MCs was associated with worst survival. In a radial distance of 10µm, 20µm, and 40µm, a higher infiltration of CTLs PD-1+, was observed in the group of recurrence than non-recurrence group, surrounding MCs PD-L1 negative (AUC 0.49, 3.80, and 20.03; vs AUC 0.01, 0.16, and 1.29, respectively), and MCs PD-L1 positive (AUC 0.60, 4.35, and 19.90; vs AUC 0.01, 0.20, and 2.20, respectively). A high infiltration of CTLs PD-1+ surrounding MCs, with or without expression of PD-L1, was associated with worse survival. All the differences were statistically significant (P&amp;lt;0.05). Conclusion. Close spatial proximity of antigen-experienced CTLs and TAMs PD-L1+ to MCs are associated with recurrence and poor survival in early stages of NSCLC. We determined that ITH of immune cell densities is associated with recurrence of surgically resected NSCLC. Tumor-immune cell spatial modeling offers a deep understanding of tumor microenvironment that impacts on clinical outcomes. Supported by CPRITRP160668 and UT Lung SPORE grants Citation Format: Alejandro Francisco-Cruz, Edwin R. Parra, Santhoshi N. Krishnan, Souptik Barua, Mei Jiang, Junya Fujimoto, Christine B. Peterson, Priyam Das, Chi-Wan Chow, Jaime Rodriguez-Canales, Carmen Behrens, Neda Kalhor, Annikka Weissferdt, John Heymach, Stephen Swisher, Boris Sepesi, Arvind Rao, J. Jack Lee, Cesar Moran, Andrew Futreal, Jianjun Zhang, Ignacio I. Wistuba. Impact of the spatial analysis of tumor-associated lymphocytes and tumor-associated macrophages on recurrence at early stage of non-small cell lung 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 1180.