Abstract NG08: Transcriptional and metabolic dynamics of cancer cells under nutrient deprivation

Cancer is an evolutionary disease driven by molecular alterations in cancer cells and concomitant tumor microenvironments. Unfortunately, cancer cells often evolve into aggressive tumors that ultimately evade treatment. Thus, in order to improve clinical outcomes, there is an urgent need to define mechanisms by which cancer cells evolve. Recent multi-region sequencing studies, including our own, have inferred phylogenetic evolution across distinct lesions collected from patients. While these studies analyzed the extent of intratumoral heterogeneity across tumor types, the molecular determinants of cancer evolution remain unclear. For example, it is challenging to precisely quantify the adaptive dynamics of a cancer cell lineage before, during, and after a selective pressure. Moreover, tumor microenvironments tend to be spatially and temporally heterogeneous, which complicates evolutionary analyses of cancer cells within these microenvironments. To address these challenges in resolving the evolutionary dynamics of cancer cells, our current work combined bioreactor culturing, longitudinal sampling, single cell sequencing, and metabolomics. Cancer cell lines were selected to represent diverse hematological and solid tumor types, including leukemia, lymphoma, myeloma, colorectal, retinoblastoma, and lung cancers. For four weeks, we consistently maintained multiple environmental parameters of each cancer cell population including temperature, pH, oxygen, and agitation. All cancer cell populations were initiated with the same seeding density in identical media. Since we aimed to quantify growth patterns and to define mechanisms by which cancer cells adapt to nutrient starvation, we allowed each cancer cell population to alter cell density as well as metabolite consumption over the course of the experiment. Every 48 hours, cells and media were collected and preserved to establish a “fossil record” for analysis, and cell density and viability were measured. We found that all cancer cell populations demonstrated exponential growth, plateau and death phases over the course of these experiments, and that each cell line exhibited its own characteristic growth pattern and carrying capacity (range 125 - 250 million cancer cells) despite all cell lines having been grown in the same environmental condition. Moreover, these growth patterns were highly concordant among independently maintained populations. Given our environmental controls, these results suggest that the cancer cell population growth patterns we observed reflected cell-intrinsic features. To explore transcriptional dynamics, we used single cell RNA sequencing to analyze longitudinal samples of the cancer cells. We found that transcriptional subclones emerged over the course of the experiment with altered gene expression profiles, including in genes with functions related to cancer cell metabolism such as biosynthesis, stress responses, and nutrient uptake, indicating putative mechanisms by which the cancer cells were adapting to an increasingly stringent environment. To further define environmental constituents, we analyzed longitudinal media samples that were collected at each timepoint with the cancer cells. Multiple metabolites were consumed within the first seven days of culture, including amino acids, vitamins, and nucleotides. Strikingly, we also observed metabolites that were secreted into the media over the course of the experiment, including nucleotides and signaling molecules. These metabolite patterns were consistent with the concomitant gene expression changes of the cancer cells. Overall, our results showed that the cancer cells were simultaneously adapting to and remodeling their environment rather than solely depleting nutrients. Defining such dynamics, especially in the context of fluctuating environmental conditions, will be essential for mechanistic studies of cancer evolution.

Citation Format: Alvin P. Makohon-Moore. Transcriptional and metabolic dynamics of cancer cells under nutrient deprivation. [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 NG08.

Abstract 2148: Robust detection of somatic genetic alterations in pancreatic cancer ascites

Introduction: Regardless of the stage at diagnosis most patients with pancreatic ductal adenocarcinoma develop peritoneal disease and some malignant ascites (MA) as well. Prior studies have shown that MA negatively affects overall treatment efficacy and survival. Despite the clinical significance of MA it has not been studied to any great extent.

Methods: We collected MA and matched normal tissue samples at autopsy from 20 PDAC patients who were initially diagnosed at stages IIB to IV. Whole exome or targeted sequencing was previously performed on each PDAC. Each MA sample was centrifuged twice at 4000 RPM first and then at 15000 RPM to separate the cell pellet (CP) from the cell-free ascites fluid. We next extracted DNA from the CP, matched normal tissue, and the cell-free DNA (cfDNA) from the ascites fluid, and all were submitted to the Genomics Core for MSK-IMPACT, a targeted cancer gene panel representing 505 genes.

Results: Results of the first five patients are complete and the remaining are in process. Comparison of the CPs and/or cfDNA to the matched tumor samples indicated 100% concordance for detected variants. However, the somatic alterations of the CP specifically versus the matched cfDNA were divergent in all patients analyzed thus far. Virtually all copy number alterations in all patients were deep deletions (range 66 to 187 cancer genes deleted) affecting multiple DNA repair pathways including homologous recombination deficiency and microsatellite repair.

Conclusions: Samples of MA, when both the cell pellet and cfDNA are sequenced, accurately represent the genetic features of the matched PDAC tissue and may serve as an alternative mode of sampling for precision medicine. Differences in the genetics of the CP versus the cfDNA suggest polyclonality in the peritoneal space. Moreover, the finding of deep deletions in targetable DNA repair pathways suggest a therapeutic vulnerability for exploration. Given that paracentesis is often performed in the palliative setting and may be performed multiple times over the course of a patients’ management, it also offers an opportunity to determine how clonal dynamics in the peritoneal space change over time. Patients with MA have poor overall survival compared to patients without MA so these patients may benefit from this type of tracking which could potentially help with their treatment.

Citation Format: Rajya L. Kappagantula, Alvin P. Makohon-Moore, Shigeaki Umeda, Elias-Ramzey R. Karnoub, Jerry P. Melchor, Laura D. Wood, Christine A. Iacobuzio-Donahue. Robust detection of somatic genetic alterations in pancreatic cancer ascites [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 2148.

Evidence for reduced BRCA2 functional activity in Homo sapiens after divergence from the chimpanzee-human last common ancestor

We performed a comparative analysis of human and 12 non-human primates to identify sequence variations in known cancer genes. We identified 395 human-specific fixed non-silent substitutions that emerged during evolution of human. Using bioinformatics analyses for functional consequences, we identified a number of substitutions that are predicted to alter protein function; one of these mutations is located at the most evolutionarily conserved domain of human BRCA2.

Pancreatic cancer prognosis is predicted by an ATAC-array technology for assessing chromatin accessibility

Unlike other malignancies, therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. Here we report tumor-cell-intrinsic chromatin accessibility patterns of treatment-naïve surgically resected PDAC tumors that were subsequently treated with (Gem)/Abraxane adjuvant chemotherapy. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we show here the discovery of a signature of 1092 chromatin loci displaying differential accessibility between patients with disease free survival (DFS) < 1 year and patients with DFS > 1 year. Analyzing transcription factor (TF) binding motifs within these loci, we identify two TFs (ZKSCAN1 and HNF1b) displaying differential nuclear localization between patients with short vs. long DFS. We further develop a chromatin accessibility microarray methodology termed "ATAC-array", an easy-to-use platform obviating the time and cost of next generation sequencing. Applying this methodology to the original ATAC-seq libraries as well as independent libraries generated from patient-derived organoids, we validate ATAC-array technology in both the original ATAC-seq cohort as well as in an independent validation cohort. We conclude that PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

The Genetic Evolution of Treatment-Resistant Cutaneous, Acral, and Uveal Melanomas

PURPOSE

Melanoma is a biologically heterogeneous disease composed of distinct clinicopathologic subtypes that frequently resist treatment. To explore the evolution of treatment resistance and metastasis, we used a combination of temporal and multilesional tumor sampling in conjunction with whole-exome sequencing of 110 tumors collected from 7 patients with cutaneous (n = 3), uveal (n = 2), and acral (n = 2) melanoma subtypes.

EXPERIMENTAL DESIGN

Primary tumors, metastases collected longitudinally, and autopsy tissues were interrogated. All but 1 patient died because of melanoma progression.

RESULTS

For each patient, we generated phylogenies and quantified the extent of genetic diversity among tumors, specifically among putative somatic alterations affecting therapeutic resistance.

CONCLUSIONS

In 4 patients who received immunotherapy, we found 1-3 putative acquired and intrinsic resistance mechanisms coexisting in the same patient, including mechanisms that were shared by all tumors within each patient, suggesting that future therapies directed at overcoming intrinsic resistance mechanisms may be broadly effective.

Abstract LB-263: Pancreatic cancer prognosis is predicted by chromatin accessibility microarray

Personalized therapy is the future of cancer care. Almost half of the cancer patients do not respond to chemotherapy. For instance, pancreatic ductal adenocarcinoma (PDAC) patients with the limited local disease and with no detectable metastasis typically have their primary tumor surgically resected, but the disease recurs in approximately 50% of cases within 1 year of surgery, in spite of adjuvant chemotherapy. Although gene expression signatures correlating prognosis have been described in PDAC, the therapeutic utility of these signatures has been limited based in part on a large number of genes displaying an altered expression. On the other hand, regulatory regions common to these genes might be amenable to collective epigenetic reprogramming using epigenetic drugs. We interrogated genome-wide chromatin accessibility using Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) on EpCAM+ PDAC malignant cells sorted from a cohort of 54 treatment-naïve resected tumors, in hopes of defining a tumor-intrinsic chromatin signature associated with recurrence. We discovered a signature of 1092 loci that were differentially accessible between recurrent (disease-free survival (DFS) &lt; 1 year) and non-recurrent patients (DFS &gt; 1 year). Through transcription factor (TF) binding motif analysis, we identified candidate TFs whose accessible motifs were differentially associated with recurrence. Nuclear localization of two such TFs, ZKSCAN1 and HNF1b, were assessed by immunostaining on tissue microarrays (TMA) representing 40 out of 54 patients. Nuclear staining of HNF1b was strong in tumor tissue from non-recurrent patients and weak or absent in recurrent patients, but ZKSCAN1 staining patterns were not significantly associated with recurrence. In a TMA representing an independent PDAC cohort (n=97) preselected for 52 long (OS 6 years)- and 45 short (OS 6 months)- term survivors, the number of nuclear positive cells for HNF1b was 52-fold higher in the long-term compared to the short-term survivors and that for ZKSCAN1 was 5.3-fold higher in the short-term compared to the long-term survivors. We further validated the 1092 chromatin accessibility signature by a novel microarray-based platform technology that we termed “ATAC-Array”, where the differentially accessible regions from the signatures were probed on a glass slide and then hybridized with fluorescent-labeled ATAC-libraries. This is a cost-effective, easy-to-use platform technology avoiding the time and cost of next-generation ATAC library sequencing. ATAC-array is the only microarray that reads chromatin accessibility. We have compared ATAC-array side-by-side with ATAC-seq (n=30) and found significant correlation (Pearson's median r= 0.64, range= 0.50- 0.77). By performing ATAC-array on the PDAC cohort (n=38), we have independently re-classified the patients who recurred early and the ones who did not (Gehan-Breslow-Wilcoxon test p=0.0076). ATAC-array, as the technology itself, has enormous potential for a wide range of applications, and we propose to develop it as a clinically validated theragnostic tool to predict and stratify cancer patients for epigenetic therapy.

Citation Format: Surajit Dhara, Sagar Chhangawala, Himanshu Chintalapudi, Alexandra L. Massa, Victoria Aveson, Gokce Askan, Liguo Zhang, Remy Nicolle, Alvin P. Makohon-Moore, Smrita Sinha, Jiang Gui, Richard Moffitt, Kenneth H. Yu, Vinod Balachandran, Rohit Chandwani, Christina Leslie, Steven D. Leach. Pancreatic cancer prognosis is predicted by chromatin accessibility microarray [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 LB-263.

The Evolutionary Origins of Recurrent Pancreatic Cancer

Surgery is the only curative option for stage I/II pancreatic cancer; nonetheless, most patients will experience a recurrence after surgery and die of their disease. To identify novel opportunities for management of recurrent pancreatic cancer, we performed whole-exome or targeted sequencing of 10 resected primary cancers and matched intrapancreatic recurrences or distant metastases. We identified that recurrent disease after adjuvant or first-line platinum therapy corresponds to an increased mutational burden. Recurrent disease is enriched for genetic alterations predicted to activate MAPK/ERK and PI3K-AKT signaling and develops from a monophyletic or polyphyletic origin. Treatment-induced genetic bottlenecks lead to a modified genetic landscape and subclonal heterogeneity for driver gene alterations in part due to intermetastatic seeding. In 1 patient what was believed to be recurrent disease was an independent (second) primary tumor. These findings suggest routine post-treatment sampling may have value in the management of recurrent pancreatic cancer. SIGNIFICANCE: The biological features or clinical vulnerabilities of recurrent pancreatic cancer after pancreaticoduodenectomy are unknown. Using whole-exome sequencing we find that recurrent disease has a distinct genomic landscape, intermetastatic genetic heterogeneity, diverse clonal origins, and higher mutational burden than found for treatment-naïve disease.See related commentary by Bednar and Pasca di Magliano, p. 762.This article is highlighted in the In This Issue feature, p. 747.

A unifying paradigm for transcriptional heterogeneity and squamous features in pancreatic ductal adenocarcinoma

Pancreatic cancer expression profiles largely reflect a classical or basal-like phenotype. The extent to which these profiles vary within a patient is unknown. We integrated evolutionary analysis and expression profiling in multiregion-sampled metastatic pancreatic cancers, finding that squamous features are the histologic correlate of an RNA-seq-defined basal-like subtype. In patients with coexisting basal and squamous and classical and glandular morphology, phylogenetic studies revealed that squamous morphology represented a subclonal population in an otherwise classical and glandular tumor. Cancers with squamous features were significantly more likely to have clonal mutations in chromatin modifiers, intercellular heterogeneity for MYC amplification and entosis. These data provide a unifying paradigm for integrating basal-type expression profiles, squamous histology and somatic mutations in chromatin modifier genes in the context of clonal evolution of pancreatic cancer.

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 in driver 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 44 patients. 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.

Minimal functional driver gene heterogeneity among untreated metastases

Metastases are responsible for the majority of cancer-related deaths. Although genomic heterogeneity within primary tumors is associated with relapse, heterogeneity among treatment-naïve metastases has not been comprehensively assessed. We analyzed sequencing data for 76 untreated metastases from 20 patients and inferred cancer phylogenies for breast, colorectal, endometrial, gastric, lung, melanoma, pancreatic, and prostate cancers. We found that within individual patients, a large majority of driver gene mutations are common to all metastases. Further analysis revealed that the driver gene mutations that were not shared by all metastases are unlikely to have functional consequences. A mathematical model of tumor evolution and metastasis formation provides an explanation for the observed driver gene homogeneity. Thus, single biopsies capture most of the functionally important mutations in metastases and therefore provide essential information for therapeutic decision-making.

Reconstructing metastatic seeding patterns of human cancers

Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumour samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumour heterogeneity among distinct samples. In silico benchmarking on simulated tumour phylogenies across a wide range of sample purities (15–95%) and sequencing depths (25-800 × ) demonstrates the accuracy of Treeomics compared with existing methods.

Tumours frequently metastasize to multiple anatomical sites and understanding how these different metastases evolve may be important for therapy. Here, the authors develop a method—Treeomics—that can construct phylogenies from multiple metastases from next-generation sequencing data.

Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer

The extent of heterogeneity among driver gene mutations present in naturally occurring metastases-that is, treatment-naive metastatic disease-is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease.

Abstract 2374: Reconstructing the evolutionary history of metastatic cancers

The evolution of metastases is responsible for 90% of cancer-related deaths. Genome wide sequencing and phylogenomic methods enable the reconstruction of the evolutionary history of a patient's cancer at unprecedented depth. However, due to a lack of samples from multiple spatially-distinct metastases from untreated patients and a lack of phylogenomic tools applicable to noisy and impure sequencing samples, the evolutionary rules governing metastatic spread have remained poorly understood.

We performed whole-genome sequencing (coverage: median 51x) as well as deep targeted sequencing (coverage: median 347x) on 21 samples from multiple regions of the primary tumor and many distinct liver and lung metastases of two treatment-naïve pancreatic ductal adenocarcinoma patients. We developed a tool, called Treeomics, that leverages computational and statistical advances to reconstruct the phylogeny of a cancer with commonly available sequencing technologies. Treeomics employs a uniquely-designed Bayesian inference model to account for error-prone sequencing and varying low neoplastic cell content (estimated purities 16-44%) to calculate the probability that a specific variant is present or absent in each sequenced lesion. Based on Mixed Integer Linear Programming, a mathematically guaranteed optimal evolutionary tree is produced.

We obtained robust phylogenies consistent with the biological processes underlying cancer evolution. The reconstructed phylogenies show that advanced cancer cells of related subclones were equally capable of seeding lung and liver metastases. Treeomics identified sequencing and biological artifacts such as those resulting from insufficient coverage or loss of heterozygosity; almost 7% of the variants were misclassified by conventional methods. Among the identified false-negatives was the common clonal driver mutation in KRAS within a region that has low sequencing read alignability and a significantly reduced coverage. Such artifacts can skew phylogenies by creating illusory tumor heterogeneity among distinct samples. Additionally, we reanalyzed publicly available data from ovarian, prostate and skin cancers. We further illuminated evolutionary relationships among some samples in a conclusive fashion and show that classical distance-based phylogenetic methods can produce evolutionarily implausible results. Treeomics avoids these common pitfalls and infers robust phylogenies confirmed by high bootstrapping values.

The new approach described here efficiently reconstructs the evolutionary history of metastases, detects potential artifacts in noisy high-throughput sequencing data, and finds subclones of distinct origin. These phylogenies shed new light on seeding patterns and metastatic progression, which has significant implications for clinical decision making and may provide predictive value for a patient's prognosis.

Citation Format: Johannes G. Reiter, Alvin P. Makohon-Moore, Jeffrey M. Gerold, Ivana Bozic, Krishnendu Chatterjee, Christine A. Iacobuzio-Donahue, Bert Vogelstein, Martin A. Nowak. Reconstructing the evolutionary history of metastatic cancers. [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 2374.