Tumor Subclones Research Articles

Abstract 6216: Single cell DNA sequencing of BRAF treatment resistant anaplastic thyroid cancer

Abstract Anaplastic thyroid cancer (ATC) is one of the most lethal cancers. Although dramatic responses to BRAFV600E-mutated ATC are seen with BRAF/MEK inhibition, treatment resistance inevitably develops, limiting survival. In this study we sequentially profiled BRAFV600E-mutated ATC at diagnosis, after BRAF/MEK targeted therapy and at the time of disease recurrence using both bulk and single-cell DNA/RNA sequencing. We profiled (~400-800 single cells) for each patient - Patient 1 (n = 704 cells); Patient 2 (n = 817 cells) and Patient 3 (n = 407 cells). At diagnosis, we show that tumor cell populations were characterized by a predominance of arm-level aneuploidies. Across all patients, there is a sharp decline in tumor cells post BRAF-targeted treatment. Interestingly, we observe at least 2 distinct tumor subclones present in the pre-treatment tumor and subsequently there was an expansion event that occurred in each patient after BRAF treatment. This was associated with acquiring unique copy number aberrations (CNA)events and the dominance of these subclones in the recurrent disease. For Patient 2, we also performed single-cell RNA sequencing and show that the recurrent tumor cells have high proliferation and stem-cell like cell states even though they had higher differentiation scores. Importantly, correlating the scDNAseq identified CNA with the inferred CNA from scRNAseq, we show proof of concept that copy number aberrations can be directly correlated with gene expression changes and gene dosage effects. Collectively our data reveal an early polyclonal dissemination model of clones in BRAF-mutated ATCs and suggests that treatment resistance to BRAF inhibition develops as a results of incomplete elimination of viable tumor cell reservoirs in ATC. Citation Format: Aatish Thennavan, Maxime Tarabichi, Per Wu, Meghan Martin, Ramona Dadu, Maria Cabanillas, Nafia Busaidy, Ying C. Henderson, Mark Zafereo, Michelle D. Williams, Stephen Lai, Nicholas Navin, Jennifer R. Wang. Single cell DNA sequencing of BRAF treatment resistant anaplastic thyroid cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6216.

Abstract 1200: A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution

Abstract Both single nucleotide variants (SNVs) and somatic copy number alterations (SCNAs) accumulate in cancer cells during tumor development, fuelling clonal evolution. However, accurate inference of their coevolution from bulk DNA sequencing is challenging. We present ALPACA (ALlele-specific Phylogenetic Analysis of clone Copy number Alterations), a novel algorithm to allow the practical inference of SNV and SCNA coevolution. ALPACA is framed as an optimisation problem, that takes as input bulk tumor sample copy number mixtures and the tumor phylogenetic tree constructed from SNVs, and deconvolves the optimal, allele-specific integer copy number profiles for every distinct clone present in the tumor. To circumvent the challenge of joint SNV/SCNA inference, we postulate that in high mutation burden tumors all relevant SCNA clones are identifiable by their unique SNVs, hence ALPACA leverages phylogenetic trees constructed from bulk tumor sequencing data using SNVs. Secondly, to restrict the clone-specific copy number search space, ALPACA leverages constraints imposed by multisample sequencing, specifically in cases where clones are present across multiple samples or clones from different samples are phylogenetically related. Finally, ALPACA relies on parsimony and biologically informed constraints to further guide the deconvolution process. We demonstrate that ALPACA infers the copy number evolution of complex simulated tumors with higher accuracy than current state-of-the-art methods. We apply ALPACA to the large, multisample non-small cell lung cancer (NSCLC) cohort from the recent longitudinal, prospective TRACERx421 study, and show that ALPACA uncovers loss of heterozygosity and amplification events in minor subclones that were previously missed using standard approaches. ALPACA's assignment of SCNA driver events to branches of the phylogenetic tree reveals the evolutionary ordering of SNVs and SCNAs during NSCLC tumor evolution, such as late focal amplifications affecting the TERT gene locus occurring in subclones which expand and dominate a tumor sample. ALPACA enables an in-depth analysis of the coevolution of mutations and SCNAs in the tumor’s evolutionary history, revealing distinct patterns of copy number evolution. Notably, ALPACA identifies common patterns of copy number changes across the genome characterizing metastatic seeding clones, revealing that they harbor an increased number of SCNAs compared to clones that do not metastasize. Additionally, ALPACA uncovers subclonal enrichment for CCND1 amplification in primary tumor subclones that seed metastasis, and an overall increase of SCNA events occurring in both tumors with polyclonal seeding and extrathoracic metastases. Clone-level results obtained with ALPACA can offer new clinical insights and enable new types of analysis, e.g. copy number signature analysis including temporal order of SCNA acquisition. Citation Format: Piotr Pawlik, Kristiana K. Grigoriadis, Abigail Bunkum, Simone Zaccaria, Nicholas McGranahan, Charles Swanton. A novel algorithm for deconvolving cancer allele-specific clone copy number and copy number evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1200.

HER2 and PD-L1 Expression in Gastric and Gastroesophageal Junction Cancer: Insights for Combinatorial Targeting Approaches.

Gastric and gastroesophageal junction adenocarcinomas (GA/GEJA) are associated with a poor prognosis, primarily due to late disease diagnosis. Human Epidermal Growth Factor Receptor 2 (HER2) overexpression and programmed death-ligand 1 (PD-L1) expression are important biomarkers for treatment selection in locally advanced unresectable and metastatic GA/GEJA, and there is increasing interest in their role in earlier stages of disease. In this study, we aimed to evaluate HER2 and PD-L1 expression in a curative-intent GA/GEJA cohort to describe their expression patterns and analyze the association between HER2 expression and clinicopathological features. HER2 expression was evaluated in surgical and endoscopic submucosal dissection tumor samples, and PD-L1 was evaluated in HER2-positive cases. The clinical cohort included 107 patients, with 8.4% testing positive for HER2 (seven of whom also exhibited a PD-L1 combined positive score of ≥1. HER2 status was not significantly associated with survival outcomes. A pathologist-guided, region-specific analysis revealed that PD-L1 expression rarely overlaps with HER2-positive tumor areas. While the therapeutic implications of these observations remain unknown, these findings suggest that combination strategies targeting HER2 and PD-L1 might be directed toward distinct tumor subclones. The herein disclosed region-specific biomarker expression patterns may have important therapeutic and prognostic impacts, warranting further evaluation.

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

Modifying the electrical, optical, and magnetic properties of cancer cells: A comprehensive approach for cancer management

AbstractDespite the recent successes of cancer therapy, numerous obstacles remain. The medical community of the 16th century believed that magnets might be used to cure or prevent illness. However, this concept has only recently been put into practice in the treatment of cancer. Cancers vary greatly not only at the patient, tissue, and cellular levels but also at the molecular level. Because of this multiscale heterogeneity, effective treatments that not only differentiate between cancerous and healthy tissues but also target a wide variety of tumor subclones are difficult to develop. Most treatments either take advantage of a specific biological characteristic shared by cancer cells (e.g., their propensity for rapid division) or indiscriminately eradicate every cell in an area of interest. In this article, we review the physical, chemical, electrical, optical, and magnetic properties of cancer cells, before discussing how these properties may be modulated by current and future cancer therapies.

Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination

BackgroundEvolutionary models of breast cancer progression differ on the extent to which metastatic potential is pre-encoded within primary tumors. Although metastatic recurrences often harbor putative driver mutations that are not detected in their antecedent primary tumor using standard sequencing technologies, whether these mutations were acquired before or after dissemination remains unclear.MethodsTo ascertain whether putative metastatic driver mutations initially deemed specific to the metastasis by whole exome sequencing were, in actuality, present within rare ancestral subclones of the primary tumors from which they arose, we employed error-controlled ultra-deep sequencing (UDS-UMI) coupled with FFPE artifact mitigation by uracil-DNA glycosylase (UDG) to assess the presence of 132 “metastasis-specific” mutations within antecedent primary tumors from 21 patients. Maximum mutation detection sensitivity was ~1% of primary tumor cells. A conceptual framework was developed to estimate relative likelihoods of alternative models of mutation acquisition.ResultsThe ancestral primary tumor subclone responsible for seeding the metastasis was identified in 29% of patients, implicating several putative drivers in metastatic seeding including LRP5 A65V and PEAK1 K140Q. Despite this, 93% of metastasis-specific mutations in putative metastatic driver genes remained undetected within primary tumors, as did 96% of metastasis-specific mutations in known breast cancer drivers, including ERRB2 V777L, ESR1 D538G, and AKT1 D323H. Strikingly, even in those cases in which the rare ancestral subclone was identified, 87% of metastasis-specific putative driver mutations remained undetected. Modeling indicated that the sequential acquisition of multiple metastasis-specific driver or passenger mutations within the same rare subclonal lineage of the primary tumor was highly improbable.ConclusionsOur results strongly suggest that metastatic driver mutations are sequentially acquired and selected within the same clonal lineage both before, but more commonly after, dissemination from the primary tumor, and that these mutations are biologically consequential. Despite inherent limitations in sampling archival primary tumors, our findings indicate that tumor cells in most patients continue to undergo clinically relevant genomic evolution after their dissemination from the primary tumor. This provides further evidence that metastatic recurrence is a multi-step, mutation-driven process that extends beyond primary tumor dissemination and underscores the importance of longitudinal tumor assessment to help guide clinical decisions.

Abstract A007: Representative sampling of invasive breast carcinomas: Interim report from a prospective study (HOLST-F)

Abstract Background: Although a range of therapeutic options are available in the management of invasive breast carcinomas, spatial segregation of tumour subclones has hampered biomarker identification in single-region samples. Representative sampling (RS) overcomes spatial bias by sampling from a homogenized and well-mixed cancer specimen. The Homogenization of Leftover Surgical Tissue Feasibility Study (HoLST-F - NCT03832062) is a prospective trial aiming to assess the feasibility of RS in tumor tissue leftover after pathology sampling. An interim analysis of the breast cancer cohort is presented. Methods: In the context of the HoLST-F study and pre-specified end-points, representative samples derived from 75 leftover invasive breast carcinoma specimens underwent flow cytometric analysis of CK8/18, CD3, Ki67 and DAPI. Tumor cell enrichment by CK8/18 positivity and ploidy (in aneuploid carcinomas) was performed for downstream DNA extraction and whole exome sequencing. Somatic variants were determined using a bespoke pipeline to remove artefacts associated with fixation. Variant oncogenicity and therapeutic evidence levels were assigned by OncoKB variant annotation. Quantitative image analysis was applied to tissue sections from diagnostic FFPE blocks stained with Ki67 immunohistochemistry (n=78) and H&E for lymphocytic infiltration scores (n=175) to correlate with flow cytometry. Results: In enriched representative samples, oncogenic mutations were commonly identified at high variant allele frequency (VAF) in known breast carcinoma driver genes including PIK3CA, CDH1, TP53, KMT2C and GATA3. Other clinically relevant oncogenic mutations were identified in ESR1, PTEN, ERBB2, RB1, AKT1, BRCA1, NF1 and FOXA1 which have been associated with resistance to various anti-cancer therapies. These mutations occurred at low and high VAFs indicative of both of clonal and sub-clonal resistance mechanisms. Recurrent variants in ESR1 (e.g. D538G) and PIK3CA (e.g. H1047R/L) were associated with Level 1 evidence for use as predictive biomarkers, while variants in twelve other genes across the cohort were associated with Level 2-4 evidence. Lymphocyte infiltration scores and Ki67 expression varied by tumor region, however RS by flow cytometry showed strong correlation with a weighted average across multiregional quantification of Ki67 expression (R=0.81, p=2.8 × 10-8) and lymphocyte infiltration (R=0.61, p<2.2 × 10-16). Conclusions: RS of invasive breast carcinoma in the HoLST-F trial has recapitulated the expected genomic driver landscape in breast cancer, in addition to identifying both clonal and subclonal genomic mechanisms of therapy resistance. Many of these mutations are either current or emerging therapeutic targets. Flow quantification of cells expressing phenotypic biomarkers (Ki67 and CD3) is feasible through RS and early analysis indicates that RS correlates with a weighted average across multiple regions. Leftover surgical tissue is an underutilized resource for biomarker assessment in breast carcinomas and can be examined by RS. Citation Format: Brian Hanley, Lisa Gallegos, Lavinia Spain, Husayn Pallikonda, Zayd Tippu, Samantha Hill, Aoune Barhoumi, Fiona Byrne, Yulia Dogva, Ashley Gilchrist, Glenn Noel-Storr, Hannah Veloz, Stacey Stanislaw, Harold Sansano, Kim Edmonds, Eleanor Carlyle, Nicholas Turner, James Larkin, Nelson Alexander, Samra Turajlic. Representative sampling of invasive breast carcinomas: Interim report from a prospective study (HOLST-F) [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A007.

Abstract A006: Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value

Abstract Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Understanding the evolution of an individual PrCa through serial analysis in space and time may be more important than identifying actionable targets for therapy from single samples as in current practice. The most prominent recent example of this is our recent evolution-based discovery of subclone eradication in a metastatic PrCa, with subsequent identification of a novel method to compare eradicated and resistant subclones to better resolve actionable targets for therapy. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, five years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, three years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases. Taken together with our recent discovery that solid tumor subclones can be eradicated, and that comparison of eradicated and resistant subclones could guide therapy, we believe the case for embarking on clinical trials testing evolutionary-analysis informed PrCa care is compelling. PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value. Citation Format: Anssi Nurminen, Serafiina Jaatinen, Sinja Taavitsainen, Gunilla Högnäs, Tom Lesluyes, Naser Ansari-Pour, Teemu Tolonen, Kerstin Haase, Antti Koskenalho, Matti Kankainen, Juho Jasu, Hanna Rauhala, Jenni Kesäniemi, Tiia Nikupaavola, Paula Kujala, Irina Rinta-Kiikka, Jarno Riikonen, Antti Kaipia, Teemu Murtola, Teuvo L. Tammela, Tapio Visakorpi, Matti Nykter, David C. Wedge, Peter Van Loo, G. Steven Bova. Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A006.

Single-cell genomics analysis reveals complex genetic interactions in an in vivo model of acquired BRAF inhibitor resistance.

The evolution of therapeutic resistance is a major obstacle to the success of targeted oncology drugs. While both inter- and intratumoral heterogeneity limit our ability to detect resistant subpopulations that pre-exist or emerge during treatment, our ability to analyze tumors with single-cell resolution is limited. Here, we utilized a cell-based transposon mutagenesis method to identify mechanisms of BRAF inhibitor resistance in a model of cutaneous melanoma. This screen identified overexpression of NEDD4L and VGLL3 as significant drivers of BRAF inhibitor resistance in vivo. In addition, we describe a novel single-cell genomics profiling method to genotype thousands of individual cells within tumors driven by transposon mutagenesis. This approach revealed a surprising genetic diversity among xenograft tumors and identified recurrent co-occurring mutations that emerge within distinct tumor subclones. Taken together, these observations reveal an unappreciated genetic complexity that drives BRAF inhibitor resistance.

A germline JAK2 exon12 mutation and a late somatic CALR mutation in a patient with essential thrombocythemia.

It has been discovered that Janus kinase 2 (JAK2) exon12 mutations lead to the polycythemia vera (PV) phenotype, while somatic mutations of calreticulin (CALR) are associated with essential thrombocythemia (ET) or primary myelofibrosis. In this article, we report a case of ET with coexistence of JAK2 exon12 and CALR mutations. The objective of this study was to elucidate the pathogenicity mechanism of a JAK2 exon12 mutation (JAK2N533S) and the role of the coexistence of mutations on the hematological phenotype. We designed a colony analysis of tumor cells obtained from this patient, and attempted to identify mutant genes using DNA from hair follicles. Mutation impairment prediction and conservative analysis were conducted to predict the mutation impairment and structure of JAK2N533S. In addition, we conducted a functional analysis of JAK2N533S by constructing Ba/F3 cell models. Three distinct tumor subclones, namely JAK2N533Shet+/CALRtype1het +, JAK2N533Shet+/CALR wt, and JAK2N533Shet+/CALRtype1hom +, were identified from the 17 selected erythroid and 21 selected granulocyte colonies. The analysis of hair follicles yielded positive results for JAK2N533S. According to the bioinformatics analysis, JAK2N533S may exert only a minor effect on protein function. Functional studies showed that JAK2N533S did not have a significant effect on the proliferation of Ba/F3 cells in the absence of interleukin-3 (IL-3), similar to wild-type JAK2. Notably, there were no increased phosphorylation levels of JAK2-downstream signaling proteins, including signal transducer and activator of transcription 3 (STAT3) and STAT5, in Ba/F3 cells harboring the JAK2N533S. Our study revealed that the JAK2N533Shet+/CALRtype1het+ subclone was linked to a significant expansion advantage in this patient, indicating that it may contribute to the development of the ET phenotype. We further demonstrated that JAK2N533S, as a noncanonical JAK2 exon12 mutation, is a germline mutation that may not exert an effect on cell proliferation and protein function. These results and the present body of available data imply that certain noncanonical JAK2 mutations are not gain-of-function mutations leading to the development of myeloproliferative neoplasms.

A Bayesian framework to study tumor subclone-specific expression by combining bulk DNA and single-cell RNA sequencing data.

Genetic and gene expression heterogeneity is an essential hallmark of many tumors, allowing the cancer to evolve and to develop resistance to treatment. Currently, the most commonly used data types for studying such heterogeneity are bulk tumor/normal whole-genome or whole-exome sequencing (WGS, WES); and single-cell RNA sequencing (scRNA-seq), respectively. However, tools are currently lacking to link genomic tumor subclonality with transcriptomic heterogeneity by integrating genomic and single-cell transcriptomic data collected from the same tumor. To address this gap, we developed scBayes, a Bayesian probabilistic framework that uses tumor subclonal structure inferred from bulk DNA sequencing data to determine the subclonal identity of cells from single-cell gene expression (scRNA-seq) measurements. Grouping together cells representing the same genetically defined tumor subclones allows comparison of gene expression across different subclones, or investigation of gene expression changes within the same subclone across time (i.e., progression, treatment response, or relapse) or space (i.e., at multiple metastatic sites and organs). We used simulated data sets, in silico synthetic data sets, as well as biological data sets generated from cancer samples to extensively characterize and validate the performance of our method, as well as to show improvements over existing methods. We show the validity and utility of our approach by applying it to published data sets and recapitulating the findings, as well as arriving at novel insights into cancer subclonal expression behavior in our own data sets. We further show that our method is applicable to a wide range of single-cell sequencing technologies including single-cell DNA sequencing as well as Smart-seq and 10x Genomics scRNA-seq protocols.

Reciprocal interactions between malignant cells and macrophages enhance cancer stemness and M2 polarization in HBV-associated hepatocellular carcinoma.

Background: The tumor microenvironment of cancers has emerged as a crucial component in regulating cancer stemness and plays a pivotal role in cell-cell communication. However, the specific mechanisms underlying these phenomena remain poorly understood. Methods: We performed the single-cell RNA sequencing (scRNA-seq) on nine HBV-associated hepatocellular carcinoma (HCC) patients. The heterogeneity of the malignant cells in pathway functions, transcription factors (TFs) regulation, overall survival, stemness, as well as ligand-receptor-based intercellular communication with macrophages were characterized. The aggressive and stemness feature for the target tumor subclone was validated by the conduction of in vitro assays including sphere formation, proliferation, Annexin V apoptosis, flow cytometry, siRNA library screening assays, and multiple in vivo preclinical mouse models including mouse hepatoma cell and human HCC cell xenograft models with subcutaneous or orthotopic injection. Results: Our analysis yielded a comprehensive atlas of 31,664 cells, revealing a diverse array of malignant cell subpopulations. Notably, we identified a stemness-related subclone of HCC cells with concurrent upregulation of CD24, CD47, and ICAM1 expression that correlated with poorer overall survival. Functional characterization both in vitro and in vivo validated S100A11 as one of the top downstream mediators for tumor initiation and stemness maintenance of this subclone. Further investigation of cell-cell communication within the tumor microenvironment revealed a propensity for bi-directional crosstalk between this stemness-related subclone and tumor-associated macrophages (TAMs). Co-culture study showed that this interaction resulted in the maintenance of the expression of cancer stem cell markers and driving M2-like TAM polarization towards a pro-tumorigenic niche. We also consolidated an inverse relationship between the proportions of TAMs and tumor-infiltrating T cells. Conclusions: Our study highlighted the critical role of stemness-related cancer cell populations in driving an immunosuppressive tumor microenvironment and identified the S100A11 gene as a key mediator for stemness maintenance in HCC. Moreover, our study provides support that the maintenance of cancer stemness is more attributed to M2 polarization than the recruitment of the TAMs.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Abstract IA001: Patient-derived tumor organoids to probe the cancer immune interface

Abstract The development of rational (combination) immunotherapies is limited by an incomplete understanding of what determines a tumor’s sensitivity to immune attack. Despite great heterogeneity in resistance mechanisms between patients, functional model systems to study cancer/immune cell interactions at the level of individual patients have been lacking. Here we highlight the potential of organoid/immune cell co-cultures as individualized models of anti-tumor immunity. First, we established a co-culture platform of autologous tumor organoids and peripheral blood lymphocytes from patients with mismatch-repair deficient colorectal cancer (dMMR-CRC) and non-small-cell lung cancer (NSCLC). This allows enriching tumor-reactive T cells from peripheral blood of individual patients, and creating personalized test systems to evaluate their capacity to kill matched tumor organoids. Second, subclonal immune escape is a major barrier to achieving complete responses to cancer immunotherapies. While most tumours consist of multiple genetically distinct clones, directly investigating the potential for immune escape at the clonal level has been impossible so far, due to challenges in isolating and propagating individual tumour subclones from human cancers for functional studies. By leveraging the multi-region TRACERx study, we established multi-region organoid libraries of >20 parallel sublines from patients with NSCLC. Co-cultures of each subline with autologous tumour infiltrating lymphocytes (TIL) reveal substantial heterogeneity in the capacity of individual clonal sublines to elicit a T-cell response. We show that subclonal immune escape can be mediated by antigen-dependent and -independent mechanisms. These results show (i) that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and (ii) provide an approach to prospectively identify and isolate immune evading subclones from cancer patients. Third, analysis of a clinical cohort of patients treated with anti-PD1 therapy revealed that gamma delta T cells are critical mediators of the response in dMMR-CRC patients with genetic inactivation of beta-2-microglobulin (B2M). Co-cultures of organoids and gamma delta T cells provide direct evidence that loss of B2M increases reactivity of patient-derived gamma delta T cells towards tumor organoids. This highlights the need for functional models that move beyond conventional T cells. Future developments are directed towards establishment of complex co-culture systems to study how communication between organoids and immune cells is mediated by cell surface factors and secreted molecules, and how cellular crosstalk is altered in cancer. Citation Format: Krijn K Dijkstra. Patient-derived tumor organoids to probe the cancer immune interface [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2023 Oct 11-15; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2023;22(12 Suppl):Abstract nr IA001.

Concurrent Testing of Spatially Separated Tissue Samples and Circulating Tumor DNA Reveals Substantial Intra-Patient Genetic Heterogeneity in Relapsed/Refractory Follicular Lymphoma

Background: Scrutiny of genetic heterogeneity in follicular lymphoma (FL) patients has been mainly limited to the investigation of single-site biopsies in previous studies, while the potential of circulating cell-free DNA (cfDNA) to resolve intra-patient heterogeneity has not been fully exploited in FL. Therefore, we aimed to characterize spatiotemporal heterogeneity in relapsed/refractory (R/R) FL by performing comprehensive genomic profiling of spatially separated tissue samples with matching cfDNA samples collected throughout the disease course. Methods: We performed ultra-deep targeted sequencing of 63 tumor tissue DNA (tisDNA), 28 cfDNA and paired germline DNA samples collected from 22 R/R FL patients. Sequencing libraries were prepared using a SureSelectXT HS (Agilent, USA) panel encompassing 173 genes recurrently mutated in FL, as well as rearrangement regions for immunoglobulin V(D)J repertoire profiling. Sequencing was performed on a NovaSeq6000 or NextSeq2000 (Illumina, USA) platform reaching a median deduplicated depth of 5,419x and 1,695x for cfDNA and tisDNA samples, respectively. We called short somatic variants using GATK Mutect2 (v.4.1.7.0), copy number alterations using PureCN (v.1.20.0) and CNVKit (v.0.9.9), as well as immunoglobulin repertoire using the whole-mark module of ARResT/Interrogate. Results: Median 6 and 8 non-silent variants were detected in cfDNA and tisDNA samples, respectively, affecting KMT2D (52%), CREBBP (45%) and TNFRSF14 (33%) most frequently in both sample types. Non-silent variants were detected in 21 of 24 (87.5%) pretreatment cfDNA samples. Comparing tisDNA samples with matching pretreatment cfDNA samples median 63.6% of variants were shared, yet unique variants were identified in cfDNA in 13/20 sample pairs, involving a median 14.3% of the variants. Studying the phylogenetic evolution of tumor samples pointed to early branching in majority of the patients, with ubiquitously present mutations detected in all samples constituting a median 24.3% of variants, although late branching was also observed in a subset (2/22) of the patients with at least 50% of variants detected in all samples. Most conserved variants were detectable in KMT2D and CREBBP, with notable exceptions of a lower mutation prevalence, but a high conservation rate in ATP6V1B2 and STAT6 genes. Subclonal clustering of variants and hierarchy analysis of samples from patients (n=5) with 2 tisDNA collected at separate lymphoma sites and a matching pretreatment cfDNA indicated that spatially discordant variants formed the same subclone, that could be also recovered in cfDNA in 4/5 patients (80%). An additional patient presented with almost identical tisDNA samples, but further unique mutations in cfDNA (PAT-FL-20)(Figure 1.). Investigating the prognostic significance of ctDNA level in the relapsed setting revealed that higher ctDNA levels were significantly associated with poor response to therapy (p=0.023, Kruskal-Wallis test), yet when we stratified patients by the median pretreatment ctDNA level (1.44x10 5 haploid genome equivalent/mL plasma) progression free survival in the subsequent treatment line was not substantially different between the two arms (p=0.11, log-rank test). Conclusion: Based on our results, R/R FL is characterized by remarkable intra-patient genetic heterogeneity. Although the founder clone harboring pathogenic KMT2D and CREBBP mutations can be identified in majority of the samples, expansion of tumor subclones between lymphoma sites confers divergent evolution, leaving genetic alterations unidentified during single-site based genetic testing. We also provide preliminary evidence, that multitarget high-throughput sequencing of cfDNA can uncover spatially restricted subclones that play a role in disease progression in R/R FL and that pretreatment ctDNA level might have a predictive value in the relapsed setting of FL. Figure 1. Molecular alterations in FL patients with tisDNA samples from two separate lymphoma sites and a matching cfDNA. KMT2D and CREBBP variants show high conservation, yet further variants are often spatially restricted, which can be resolved by cfDNA profiling. Copy number alterations (CNA) show lower concordance, yet recurrent CNA-s can be recovered in a subset of the cases. Identical immunoglobulin heavy and light chain usage can be detected in all samples of 3 patients and in paired tisDNA in 2 patients.

Clonal Neoantigen: Emerging “Mechanism-based” Biomarker of Immunotherapy Response

Clonal mutations represent the initiating molecular defects related to cellular transition of a normal phenotype to a malignant phenotype. Molecular genomic assessment utilizing next generation and whole exome sequencing is now being increasingly applied to biomarker determination to refine the use of targeted immune therapies. Case examples followed by retrospective study assessment have convincingly demonstrated clonal neoantigens provide a relevant predictor of response to checkpoint inhibition. A meta-analysis, by Litchfield et al., of over 1000 cancer patients from 12 landmark trials demonstrated no clinical benefit to checkpoint inhibitor (CPI) therapy in correlation to high subclonal tumor mutational burden (TMB), whereas high clonal TMB was found to be significantly correlated with better overall survival (p = 0.000000029). We discuss the mechanism of clonal vs. subclonal neoantigen targeting relationship to homologous recombination proficient (HRP) profile, evidence of preclinical and clinical benefit related to clonal neoantigens, and review a novel developing therapy called Vigil®, designed to expand the clonal neoantigen targeting effector cell populations. Vigil® is an autologous cellular immunotherapy which is designed to carry the full set of personal clonal neoantigens. Phase 2b results demonstrate a durable recurrence-free survival (RFS) and overall survival (OS) advantage for Vigil® in a subset ovarian cancer population with an HRP cancer profile.

CONIPHER: a computational framework for scalable phylogenetic reconstruction with error correction.

Intratumor heterogeneity provides the fuel for the evolution and selection of subclonal tumor cell populations. However, accurate inference of tumor subclonal architecture and reconstruction of tumor evolutionary histories from bulk DNA sequencing data remains challenging. Frequently, sequencing and alignment artifacts are not fully filtered out from cancer somatic mutations, and errors in the identification of copy number alterations or complex evolutionary events (e.g., mutation losses) affect the estimated cellular prevalence of mutations. Together, such errors propagate into the analysis of mutation clustering and phylogenetic reconstruction. In this Protocol, we present a new computational framework, CONIPHER (COrrecting Noise In PHylogenetic Evaluation and Reconstruction), that accurately infers subclonal structure and phylogenetic relationships from multisample tumor sequencing, accounting for both copy number alterations and mutation errors. CONIPHER has been used to reconstruct subclonal architecture and tumor phylogeny from multisample tumors with high-depth whole-exome sequencing from the TRACERx421 dataset, as well as matched primary-metastatic cases. CONIPHER outperforms similar methods on simulated datasets, and in particular scales to a large number of tumor samples and clones, while completing in under 1.5 h on average. CONIPHER enables automated phylogenetic analysis that can be effectively applied to large sequencing datasets generated with different technologies. CONIPHER can be run with a basic knowledge of bioinformatics and R and bash scripting languages.

Distinct immune escape and microenvironment between RG-like and pri-OPC-like glioma revealed by single-cell RNA-seq analysis

The association of neurogenesis and gliogenesis with glioma remains unclear. By conducting single-cell RNA-seq analyses on 26 gliomas, we reported their classification into primitive oligodendrocyte precursor cell (pri-OPC)-like and radial glia (RG)-like tumors and validated it in a public cohort and TCGA glioma. The RG-like tumors exhibited wild-type isocitrate dehydrogenase and tended to carry EGFR mutations, and the pri-OPC-like ones were prone to carrying TP53 mutations. Tumor subclones only in pri-OPC-like tumors showed substantially down-regulated MHC-I genes, suggesting their distinct immune evasion programs. Furthermore, the two subgroups appeared to extensively modulate glioma-infiltrating lymphocytes in distinct manners. Some specific genes not expressed in normal immune cells were found in glioma-infiltrating lymphocytes. For example, glial/glioma stem cell markers OLIG1/PTPRZ1 and B cell-specific receptors IGLC2/IGKC were expressed in pri-OPC-like and RG-like glioma-infiltrating lymphocytes, respectively. Their expression was positively correlated with those of immune checkpoint genes (e.g., LGALS33) and poor survivals as validated by the increased expression of LGALS3 upon IGKC overexpression in Jurkat cells. This finding indicated a potential inhibitory role in tumor-infiltrating lymphocytes and could provide a new way of cancer immune evasion.

A Bayesian method to infer copy number clones from single-cell RNA and ATAC sequencing.

Single-cell RNA and ATAC sequencing technologies enable the examination of gene expression and chromatin accessibility in individual cells, providing insights into cellular phenotypes. In cancer research, it is important to consistently analyze these states within an evolutionary context on genetic clones. Here we present CONGAS+, a Bayesian model to map single-cell RNA and ATAC profiles onto the latent space of copy number clones. CONGAS+ clusters cells into tumour subclones with similar ploidy, rendering straightforward to compare their expression and chromatin profiles. The framework, implemented on GPU and tested on real and simulated data, scales to analyse seamlessly thousands of cells, demonstrating better performance than single-molecule models, and supporting new multi-omics assays. In prostate cancer, lymphoma and basal cell carcinoma, CONGAS+ successfully identifies complex subclonal architectures while providing a coherent mapping between ATAC and RNA, facilitating the study of genotype-phenotype maps and their connection to genomic instability.

Follicular lymphoma evolves with a surmountable dependency on acquired glycosylation motifs in the B-cell receptor

AbstractAn early event in the genesis of follicular lymphoma (FL) is the acquisition of new glycosylation motifs in the B-cell receptor (BCR) due to gene rearrangement and/or somatic hypermutation. These N-linked glycosylation motifs (N-motifs) contain mannose-terminated glycans and can interact with lectins in the tumor microenvironment, activating the tumor BCR pathway. N-motifs are stable during FL evolution, suggesting that FL tumor cells are dependent on them for their survival. Here, we investigated the dynamics and potential impact of N-motif prevalence in FL at the single-cell level across distinct tumor sites and over time in 17 patients. Although most patients had acquired at least 1 N-motif as an early event, we also found (1) cases without N-motifs in the heavy or light chains at any tumor site or time point and (2) cases with discordant N-motif patterns across different tumor sites. Inferring phylogenetic trees of the patients with discordant patterns, we observed that both N-motif–positive and N-motif–negative tumor subclones could be selected and expanded during tumor evolution. Comparing N-motif–positive with N-motif–negative tumor cells within a patient revealed higher expression of genes involved in the BCR pathway and inflammatory response, whereas tumor cells without N-motifs had higher activity of pathways involved in energy metabolism. In conclusion, although acquired N-motifs likely support FL pathogenesis through antigen-independent BCR signaling in most patients with FL, N-motif–negative tumor cells can also be selected and expanded and may depend more heavily on altered metabolism for competitive survival.