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
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.
Pancreatic ductal adenocarcinoma (PDAC) is typically diagnosed after the disease has metastasized; it is among the most lethal forms of cancer. We recently described aberrant expression of an open ...reading frame 1 protein, ORF1p, encoded by long interspersed element-1 (LINE-1; L1) retrotransposon, in PDAC. To test whether LINE-1 expression leads to somatic insertions of this mobile DNA, we used a targeted method to sequence LINE-1 insertion sites in matched PDAC and normal samples. We found evidence of 465 somatic LINE-1 insertions in 20 PDAC genomes, which were absent from corresponding normal samples. In cases in which matched normal tissue, primary PDAC and metastatic disease sites were available, insertions were found in primary and metastatic tissues in differing proportions. Two adenocarcinomas secondarily involving the pancreas, but originating in the stomach and duodenum, acquired insertions with a similar discordance between primary and metastatic sites. Together, our findings show that LINE-1 contributes to the genetic evolution of PDAC and suggest that somatic insertions are acquired discontinuously in gastrointestinal neoplasms.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
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 (
= 3), uveal (
= 2), and acral (
= 2) melanoma subtypes.
Primary tumors, metastases collected longitudinally, and autopsy tissues were interrogated. All but 1 patient died because of melanoma progression.
For each patient, we generated phylogenies and quantified the extent of genetic diversity among tumors, specifically among putative somatic alterations affecting therapeutic resistance.
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.
Somatic L1 retrotransposition events have been shown to occur in epithelial cancers. Here, we attempted to determine how early somatic L1 insertions occurred during the development of ...gastrointestinal (GI) cancers. Using L1-targeted resequencing (L1-seq), we studied different stages of four colorectal cancers arising from colonic polyps, seven pancreatic carcinomas, as well as seven gastric cancers. Surprisingly, we found somatic L1 insertions not only in all cancer types and metastases but also in colonic adenomas, well-known cancer precursors. Some insertions were also present in low quantities in normal GI tissues, occasionally caught in the act of being clonally fixed in the adjacent tumors. Insertions in adenomas and cancers numbered in the hundreds, and many were present in multiple tumor sections, implying clonal distribution. Our results demonstrate that extensive somatic insertional mutagenesis occurs very early during the development of GI tumors, probably before dysplastic growth.
Despite insights gained by bulk DNA sequencing of cancer it remains challenging to resolve the admixture of normal and tumor cells, and/or of distinct tumor subclones; high-throughput single-cell DNA ...sequencing circumvents these and brings cancer genomic studies to higher resolution. However, its application has been limited to liquid tumors or a small batch of solid tumors, mainly because of the lack of a scalable workflow to process solid tumor samples. Here we optimize a highly automated nuclei extraction workflow that achieves fast and reliable targeted single-nucleus DNA library preparation of 38 samples from 16 pancreatic ductal adenocarcinoma patients, with an average library yield per sample of 2867 single nuclei. We demonstrate that this workflow not only performs well using low cellularity or low tumor purity samples but reveals genomic evolution patterns of pancreatic ductal adenocarcinoma as well.
Abstract
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.
To explore factors associated with response and resistance to anti-PD-1 therapy, we analyzed multiple disease sites at autopsy in a patient with widely metastatic melanoma who had a heterogeneous ...response.
Twenty-six melanoma specimens (four premortem, 22 postmortem) were subjected to whole exome sequencing. Candidate immunologic markers and gene expression were assessed in 10 cutaneous metastases showing response or progression during therapy.
The melanoma was driven by biallelic inactivation of
All lesions had highly concordant mutational profiles and copy number alterations, indicating linear clonal evolution. Expression of candidate immunologic markers was similar in responding and progressing lesions. However, progressing cutaneous metastases were associated with overexpression of genes associated with extracellular matrix and neutrophil function.
Although mutational and immunologic differences have been proposed as the primary determinants of heterogeneous response/resistance to targeted therapies and immunotherapies, respectively, differential lesional gene expression profiles may also dictate anti-PD-1 outcomes.
.
The KPC mouse model, driven by the Kras and Trp53 transgenes, is well regarded for faithful recapitulation of human pancreatic cancer biology. However, the extent that this model recapitulates the ...subclonal evolution of this tumor type is unknown. Here we report evidence of continuing subclonal evolution after tumor initiation that largely reflect copy number alterations that target cellular processes of established significance in human pancreatic cancer. The evolutionary trajectories of the mouse tumors show both linear and branching patterns as well as clonal mixing. We propose the KPC model and derivatives have unexplored utility as a functional system to model the mechanisms and modifiers of tumor evolution.
Anastomotic recurrences (AR) occur in 2-10% of colorectal carcinoma cases after resection of primary tumor (PT). Currently, there are no molecular data investigating their genetic profile and ...multiple theories exist about their pathogenesis. The aim of our study was to compare the genomic profile of AR to that of the patients' corresponding matched PT and, when available, to a distant metastasis (DM).
Thirty-six tumors from 14 patients were genotyped using a capture-based, next-generation assay to define the mutational status of 341 cancer-associated genes. All patients had R0 resection of their PT and AR occurred 1.1-7.0 years following PT resection. A DM or a second AR was analyzed in 8 patients. All tumors were microsatellite stable except in one patient with Lynch syndrome.
A total of 254 somatic mutations were detected including 138 mutations in the microsatellite stable (MSS) cases. The most commonly mutated genes were APC, KRAS, TP53, PIK3CA, ATM and PIK3R1. In all patients with MSS tumors the AR and PT shared between 50-100% of mutations, including mutations in key driver genes, consistent with these tumors being clonally related. Genetic events private to DM were not detected in AR and phylogenetic analysis showed that ARs were more closely related to PT than DM. In the Lynch syndrome patient the PT and AR showed distinct somatic mutations consistent with independent primaries.
ARs are clonally related to PT in sporadic colorectal carcinomas and do not appear to represent seeding of the anastomotic site by distant metastases.
Cancer immunoediting
is a hallmark of cancer
that predicts that lymphocytes kill more immunogenic cancer cells to cause less immunogenic clones to dominate a population. Although proven in mice
, ...whether immunoediting occurs naturally in human cancers remains unclear. Here, to address this, we investigate how 70 human pancreatic cancers evolved over 10 years. We find that, despite having more time to accumulate mutations, rare long-term survivors of pancreatic cancer who have stronger T cell activity in primary tumours develop genetically less heterogeneous recurrent tumours with fewer immunogenic mutations (neoantigens). To quantify whether immunoediting underlies these observations, we infer that a neoantigen is immunogenic (high-quality) by two features-'non-selfness' based on neoantigen similarity to known antigens
, and 'selfness' based on the antigenic distance required for a neoantigen to differentially bind to the MHC or activate a T cell compared with its wild-type peptide. Using these features, we estimate cancer clone fitness as the aggregate cost of T cells recognizing high-quality neoantigens offset by gains from oncogenic mutations. With this model, we predict the clonal evolution of tumours to reveal that long-term survivors of pancreatic cancer develop recurrent tumours with fewer high-quality neoantigens. Thus, we submit evidence that that the human immune system naturally edits neoantigens. Furthermore, we present a model to predict how immune pressure induces cancer cell populations to evolve over time. More broadly, our results argue that the immune system fundamentally surveils host genetic changes to suppress cancer.
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