Intra-patient Heterogeneity Research Articles

Noninvasive Assessment of Human Epidermal Growth Factor Receptor 2 (HER2) in Esophagogastric Cancer Using 89Zr-Trastuzumab PET: A Pilot Study.

Variations in human epidermal growth factor receptor 2 (HER2) expression between the primary tumor and metastases may contribute to drug resistance in HER2-positive (HER2+) metastatic esophagogastric cancer (mEGC). 89Zr-trastuzumab PET (HER2 PET) holds promise for noninvasive assessment of variations in HER2 expression and target engagement. The aim of this study was to describe HER2 PET findings in patients with mEGC. Methods: Patients with HER2+ mEGC were imaged with HER2 PET, 18F-FDG PET, and CT. Lesions were annotated using measurements (on CT) and maximum SUVs (on HER2 PET). Correlation of visualized disease burden among imaging modalities with clinical and pathologic characteristics was performed. Results: Thirty-three patients with HER2+ mEGC were imaged with HER2 PET and CT (12% esophageal, 64% gastroesophageal junction, and 24% gastric adenocarcinoma), 26 of whom were also imaged with 18F-FDG PET. More lesions were identified on 18F-FDG PET (median, 7 [range, 1-14]) than HER2 PET (median, 4 [range, 0-11]). Of the 8 lesions identified on HER2 but not on 18F-FDG PET, 3 (38%) were in bone and 1 was in the brain. Of the 68 lesions identified on 18F-FDG but not on HER2 PET, 4 (6%) were in bone and the remainder were in the lymph nodes (35, 51%) and liver (16, 24%). Of the 33 total patients, 23 (70%) were HER2 imaging-positive (≥50% of tumor load positive). Only 10 patients had 100% of the tumor load positive; 2 had 0% positive. When only patients receiving HER2-directed therapy as first-line treatment were considered (n = 13), median progression-free survival (PFS) therapy was not significantly different between HER2 imaging-positive and -negative patients. Median PFS for patients with at least 1 intense or very intense lesion (SUV ≥ 10) was 16 (95% CI: 11-not reached) mo (n = 7), compared with 12 (95% CI: 6.3-not reached) mo for patients without an intense or very intense lesion (n = 6) (P = 0.35). Conclusion: HER2 PET may identify heterogeneity of HER2 expression and allow assessment of lesions throughout the entire body. A potential application of HER2 PET is noninvasive evaluation of HER2 status including assessment of intrapatient disease heterogeneity not captured by standard imaging or single-site biopsies.

Single-Cell Multi-Omics of Peripheral Blood Reveals Tiding and Evolution of Responsive and Resistant Clones upon Daratumumab-Based Treatments in Multiple Myeloma and Plasma Cell Leukemia

Background: Treatment with anti-CD38 antibodies is a standard of care in newly diagnosed and relapsed/refractory multiple myeloma (MM). Clonal tiding and evolution as well as genomic heterogeneity are major drivers towards drug-resistant disease. However, modes of resistance to anti-CD38 directed therapies are currently unknown and might include loss of antigen expression and/or exhaustion of the immune system. We performed longitudinal single-cell multi-omic analyses of circulating tumor cells (CTC) and non-malignant cells to decipher clonal heterogeneity and tiding upon response and resistance to daratumumab (Dara)-based therapies in MM and plasma cell leukemia (PCL). Methods: Peripheral blood mononuclear cells (MNCs) were isolated from 7 patients (PCL n=5, MM n=2) before and after exposure to Dara. Samples were collected at four different time points: 1. before administration of Dara (CD38-naïve). 2. Four days after first application of Dara (CD38-exposed). 3. After relapse from Dara (CD38-refractory). 4. After an additional line of non-CD38 targeted therapy following relapse from Dara. In total, we analyzed 17 PB samples. To demonstrate that results from PB are comparable to bone marrow (BM), four paired PB and BM samples were included (21 samples in total). MNCs were subjected to single cell RNA (scRNAseq), B-cell (scBCRseq), and T-cell receptor sequencing (scTCRseq). Surface protein expression was measured using a custom panel of 57 DNA-barcoded antibodies. Sequencing files were processed with CellRanger (10x Genomics) and data were analyzed with the Seurat toolkit for single cell sequencing. Cell types were annotated with SingleR based on the Human Primary Cell Atlas built-in references. ScRepertoire was used for longitudinal scTCRseq and scBCRseq data. Copy number variations (CNVs) in CTCs were detected with inferCNV, and cellular interactions were investigated with CellPhoneDB. Results: In total, we sequenced 130.038 MNCs (PB: 108.236, range 414-8700/patient; BM: 21802, range 3375-8516/patient, Figure 1A). Malignant plasma cells were identified using scBCRseq and restricted light chain expression from scRNAseq. Even in MM patients without morphological evidence for CTC, we could identify and characterize single malignant plasma cells in PB. By inferring genome-wide CNVs from scRNAseq, we were able to characterize intra-patient genomic heterogeneity. Longitudinal tracking of CTC revealed tiding of clones characterized by distinct CNV profiles and transcriptomes upon Dara-exposure and resistance. Early transcriptional changes in CTCs upon Dara-exposure included inflammatory signaling (e.g. upregulation of IFI6, IFI35, IFIT1, IFITM1). Analysis of CD38 protein surface expression using DNA-barcoded antibodies showed significantly decreased levels after Dara exposure. To rule out that this might have resulted from competitive binding of the diagnostic antibody and Dara, we repeated analyses after discontinuing Dara and after application of a further line of therapy. In contrast to CD38 RNA expression, surface protein expression decreased significantly upon exposure and relapse, but recovered after an additional line of therapy. Expression of other druggable antigens (BCMA, SLAMF7, GPRCD5, FcRL5, Figure 1B) was not affected by treatment with Dara. Next, we investigated co-evolution of non-malignant cells. Longitudinal scTCRseq showed concomitant expansion and stagnation of TCRs. Receptor-ligand interaction analyses demonstrated that exposure to Dara resulted in significant differences in CD38-PECAM1-mediated interactions between CTCs with non-malignant B-cells and CD8+ T-cells. We detected recurrently increased immunosuppressive receptor-ligand interactions between malignant plasma cells and CD4+, CD8+, and regulatory T-cells via CD86-CTLA4 and NECTIN3-TIGIT axis upon Dara exposure. Conclusion: We demonstrate that single-cell multi-omic analyses of PB provide a minimal invasive approach to study genomic heterogeneity and evolution of malignant plasma cells and non-malignant cells of the immune system. Longitudinal analyses reveal different patterns of response and resistance to targeted myeloma therapies and might affect future therapeutic decision-making. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Multiomic Single-Cell Sequencing of Mixed Phenotypic Acute Leukemia (MPAL) Reveals Complex Immunophenotypic, Transcriptional, and Genetic Heterogeneity

Introduction Mixed phenotypic acute leukemia (MPAL) is characterized by leukemic blasts with both lymphoid and myeloid cell-surface markers. Due to the relative rarity and heterogenous nature of MPAL, the optimal therapeutic strategy remains uncertain, although emerging data suggest further sub-classification of MPAL may facilitate therapeutic decision making. Using single cell (SC) multiomic profiling, we sought to further characterize the heterogenous transcriptional, genetic, and immunophenotypic landscape of MPAL. Methods We analyzed samples from 14 patients with newly diagnosed MPAL (11 B/myeloid; 3 T/myeloid). We performed high-throughput SC DNA sequencing (Mission Bio Tapestri) and SC RNA sequencing (Fluent BioSciences PIPseq) with simultaneous cell surface immunophenotyping. Results Using SC DNA sequencing, we analyzed a total of 51,847 cells (4,196 cells/patient); using RNA sequencing, we analyzed a total of 71,579 cells (6,143 cells/patient). Multiomic SC sequencing revealed striking intra-patient heterogeneity, with multiple immunophenotypically, genetically, and/or transcriptionally distinct populations within individual patients. Furthermore, for individual patients, "mixed” phenotype was not always correlated with genetics or gene expression. In 5/14 patients, immunophenotype correlated with both genotype and transcriptional signature in at least one subpopulation. For example, in one patient, 32% of biphenotypic blasts demonstrated monocytic features (CD11b, CD14, and CD64 expression). Unlike blasts without monocytic features in the same specimen, this population was IDH2mut and had increased differential expression of LYZ and S100A8/9. For 7/14 patients, however, phenotypic populations did not correlate with a clear genetic driver. In one patient, for example, we observed two blast populations, one with an immature immunophenotype characterized by elevated CD117 and CD34 expression, and one with a monocytic immunophenotype characterized by elevated CD14 and CD64 expression. Although these two populations were both TP53mut, they had different transcriptional signatures, with the immature population showing increased SOX4, FLT3, and VPREB expression and the monocytic population with increased LYZ, S100A8/9, and MNDA expression. Finally, 2 patients had immunophenotypic heterogeneity but we observed identical genetic and transcriptional signatures within the immunophenotypically distinct subpopulations. Across this cohort, we identified a recurrent transcriptional signature associated with immature blasts, characterized by increased CD34 and CD117 expression. Found in 7 patients with either B or T/myeloid MPAL, these immature subpopulations were enriched for expression of genes associated with lymphocyte development (DNTT, VPREB, PAX5), malignant myelopoiesis (SOX4, FLT3, SPINK2), and cell-cycle regulation (TUBB, UHRF1) compared to more differentiated blasts from the same patients. Phylogenic analysis revealed the effect of mutation acquisition on development of a malignant immunophenotype. In 3 patients, we observed both heterozygous and homozygous TP53mut populations. In all 3 patients, immunophenotypically normal T cells were identified within the heterozygous TP53mut population, consistent with initial acquisition of this mutation within a stem/progenitor population. In contrast, homozygous TP53mut cells all expressed aberrant immunophenotypes, consistent with leukemic blasts. Within each individual patient, relative to the heterozygous TP53mut cells, homozygous TP53mut cells demonstrated significantly increased CD33, CD34, and CD117 expression. Conclusions Multiomic SC sequencing allows for direct measurement of immunophenotypic, genetic, and transcriptional clonal architecture. We demonstrated considerable intra- and inter-patient heterogeneity, in which both genotype and transcriptional signature, transcriptional signature alone, or neither were found to correlate with immunophenotype. Despite this heterogeneity, in half our cohort, we identified a recurrent gene expression signature associated with immature immunophenotype, which correlated with genetic drivers of immunophenotype in some cases. Future multiomic studies are needed to completely subtype MPAL and elucidate the impact of these subtypes on treatment outcomes. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Multiomic Analysis of CD38 Expression Levels in 209 Untreated and Daratumumab-Resistant Patients

The anti-CD38 antibody Daratumumab (Dara) is widely used in first-line as well as in relapsed/refractory multiple myeloma (MM). Primary or secondary resistance eventually occurs in all treated patients but the underlying mechanisms are poorly understood: Genetic alterations that lead to loss of function affecting epitopes on CD38, low baseline expression of CD38 or the selection of CD38dim cells were associated with suboptimal response to treatment. Interestingly, drugs such as all-trans retinoic acid, panobinostat or DNMT inhibitors increase Dara efficiency through reversible upregulation of CD38. Overall, three cohorts with overall 209 patients were examined for this dataset. We conducted flow cytometry in 21 therapy naïve and 19 Dara-refractory patients using a Dara epitope-specific antibody. All untreated and 11 of the resistant patients stained positive for CD38 MM, suggesting CD38 independent resistance mechanisms. In eight patients, CD38 expression was not detected; however, in five of them, additional staining with a CD38 multiepitope antibody confirmed CD38 persistence, reflecting epitope blockade through Dara or epitope mutation that interferes with the binding of the antibody. Finally, in three out of 19 refractory patients, CD38 could not be detected with both antibodies. To quantify CD38 receptor density on a molecular level, we established super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM) in the same patients. dSTORM uses fluorophore-conjugated antibodies and provides an unprecedented molecular 20 nm resolution for individual cells. We observed intra-patient heterogeneity of the CD38 receptor density with a mean expression of 35.15 ± 13.42 receptors/µm² (range 3.61-67.24) in the Dara naïve patients. Notably, in the refractory group, we found a significant decline (p=0.03) with a mean of 22.7 ± 18.26 receptors/µm² (range 17.07-63.77). In two of the three patients with no CD38 detectable, CD38 persistence could be assessed by dSTORM below the detection rate of flow cytometry. One patient remained negative for CD38, suggesting true loss of the receptor, causing Dara resistance in this patient. Next, we confirmed downregulation of CD38 gene expression using qPCR, and significantly reduced expression in the Dara refractory cohort (p=0.01). Of note, correlation between gene and receptor expression was moderate (p=0.49, r=0.57), leaving room for epigenetic regulation or posttranscriptional modification. To interrogate whether epigenetic regulation of CD38 via DNA methylation may underlie differential CD38 receptor expression, we performed deep bisulfite sequencing of MM cells and PBMCs obtained from 41 patients from our institution. CD38 on chromosome 4 contains several regulatory regions: One promoter, two adjacent promoter flanking regions and 11 enhancer regions described in ENSEMBL genome browser (GRCh38.13). The CD38 promoter was fully unmethylated (mean methylation: 0.31% ± 0.2%, range 0.2%-0.9%), but variable methylation of a CD38 promoter flanking region upstream of the promoter was detectable with 30.08% ± 17.8% (range 0.9%-61.5%) in the MM cells compared to 59.6% ± 3.9% (range 49.0%-66.7%) in the PBMCs from the same patients (p <0.001). This highlights phenotypic plasticity and suggests that DNA methylation may play a regulatory role in CD38 expression. We are currently investigating the methylome of all 14 regulatory regions in 38 Dara resistant patients (18 of them with longitudinal sampling before and after Dara therapy), 33 Dara responsive patients and 52 plasma cells obtained from healthy donors. Finally, in a cohort of 127 patients from our institution with WGS data available we screened for genetic alterations with potential impact on the CD38 receptor expression. We found monoallelic CD38 deletions in 18 patients, with one patient having an additional 11kb deletion conferring to an exon 3 loss. Exon-6 skipping, as recently described, was not detectable in the cohort. In conclusion, genetic alterations affecting the CD38 locus and true loss of the CD38 receptor are rare events and do not explain Dara resistance in most affected patients. dSTORM imaging provides additional insights in the CD38 receptor downregulation in MM patients treated with anti-CD38 moAb therapy. Regulatory mechanisms such as epigenetic regulation need to be further explored.

TMIC-37. SINGLE-CELL CHARACTERIZATION OF THE IMMUNE LANDSCAPE OF EXTREME LONG-TERM SURVIVORS WITH MALIGNANT GLIOMA

Abstract Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond two years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contribute significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and despite its dismal prognosis, small fractions of GBM patients seem to display extreme extended survival compared to the large majority of patients. The underlying mechanisms for this peculiarity remain largely unknown however, even though emerging data suggest that both cancer cell-autonomous and microenvironmental factors and their interplay probably play an important role. We used high-dimensional, multiplexed immunohistochemistry to spatially, and cytometry by time-of-flight to quantitively, characterize the cell constitution and interactions within the tumor microenvironment (TME) in 21 extreme long-term survivors (living over 10 year) and 42 deeply matched controls and therefore short-term survivors (living under 1.5 year) on a single cell level. For all tumors (epi)genetic data was also collected. We identified a high level of both inter-and intrapatient heterogeneity defined by several distinct tumoral niches, as well as described interactions within these niches and with the surrounding infiltrating immune cells of the TME in GBM. Finally, by linking patient characteristics with the heterogeneous immune composition we are able to create an immune stratification that can be linked to patient survival in GBM. Therefore, this study is an essential initial step towards strategies to alter the TME in a favorable way with a personalized modulation strategy.

Investigation of radiomics based intra-patient inter-tumor heterogeneity and the impact of tumor subsampling strategies

While radiomics analysis has been applied for localized cancer disease, its application to the metastatic setting involves a non-exhaustive lesion subsampling strategy which may sidestep the intrapatient tumoral heterogeneity, hindering the reproducibility and the therapeutic response performance. Our aim was to evaluate if radiomics features can capture intertumoral intrapatient heterogeneity, and the impact of tumor subsampling on the computed heterogeneity. To this end, We delineated and extracted radiomics features of all visible tumors from single acquisition pre-treatment computed tomography of patients with metastatic lung cancer (cohort L) and confirmed our results on a larger cohort of patients with metastatic melanoma (cohort M). To quantify the captured heterogeneity, the absolute coefficient of variation (CV) of each radiomics index was calculated at the patient-level and a sensitivity analysis was performed using only a subset of all extracted features robust to the segmentation step. The extent of information loss by six commonly used tumor sampling strategies was then assessed. A total of 602 lesions were segmented from 43 patients (median age 57, 4.9% female). All robust radiomics indexes exhibited at least 20% of variation with significant heterogeneity both in heavily and oligo metastasized patients, and also at the organ level. None of the segmentation subsampling strategies were able to recover the true tumoral heterogeneity obtained by exhaustive tumor sampling. Image-based inter-tumor intra-patient heterogeneity can be successfully grasped by radiomics analyses. Failing to take into account this kind of heterogeneity will lead to inconsistent predictive algorithms. Guidelines to standardize the tumor sampling step and/or AI-driven tools to alleviate the segmentation effort are required.

4MO Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer

De novo metastatic castration-sensitive prostate cancer (mCSPC) is highly aggressive, but the lack of routine tumour tissue in this setting hinders genomic stratification and jeopardizes precision oncology efforts. Accurate molecular profiling at diagnosis is imperative for genomics-informed risk stratification and biomarker-guided treatment. Currently, it is unclear the extent that intrapatient heterogeneity impacts clinical cancer genotyping.

Compartment-specific mutational landscape of clonal hematopoiesis

Clonal hematopoiesis (CH) is characterized by somatic mutations in blood cells of individuals without hematologic disease. While the mutational landscape of CH in peripheral blood (PB) has been well characterized, detailed analyses addressing its spatial and cellular distribution in the bone marrow (BM) compartment are sparse. We studied CH driver mutations in healthy individuals (n = 261) across different anatomical and cellular compartments. Variant allele frequencies were higher in BM than PB and positively correlated with the number of driver variants, yet remained stable during a median of 12 months of follow-up. In CH carriers undergoing simultaneous bilateral hip replacement, we detected ASXL1-mutant clones in one anatomical location but not the contralateral side, indicating intra-patient spatial heterogeneity. Analyses of lineage involvement in ASXL1-mutated CH showed enriched clonality in BM stem and myeloid progenitor cells, while lymphocytes were particularly involved in individuals carrying the c.1934dupG variant, indicating different ASXL1 mutations may have distinct lineage distribution patterns. Patients with overt myeloid malignancies showed higher mutation numbers and allele frequencies and a shifting mutation landscape, notably characterized by increasing prevalence of DNMT3A codon R882 variants. Collectively, our data provide novel insights into the genetics, evolution, and spatial and lineage-specific BM involvement of CH.

KS05.7.A Characterization of the immune composition of extreme long-term survivors with malignant glioma at single-cell level

Abstract Background Glioblastoma Multiforme (GBM) remains the most common malignant primary brain tumor with a dismal prognosis that rarely exceeds beyond two years despite extensive therapy, which consists of maximal safe surgical resection, radiotherapy and/or chemotherapy. Recently, it has become clear that GBM is not one homogeneous entity and that both intra-and intertumoral heterogeneity contribute significantly to differences in tumoral behavior which may consequently be responsible for differences in survival. Strikingly and in spite of its dismal prognosis, small fractions of GBM patients seem to display extended survival compared to the large majority of patients. The underlying mechanisms for this peculiarity remain largely unknown however, even though emerging data suggest that both cancer cell-autonomous and microenvironmental factors and their interplay probably play an important role. Material and Methods We used high-dimensional, multiplexed immunohistochemistry to spatially, and cytometry by time-of-flight to quantitively characterize the cell constitution and interactions within the tumor microenvironment (TME) in 21 extreme long-term survivors (living over ten years since primary diagnosis or five years after recurrence) and 42 deeply matched short-term controls (living under 1.5 year) on a single cell level. For all tumors (epi-)genetic data was also collected. Results We identified a high level of both inter-and intrapatient heterogeneity defined by several distinct tumor niches, as well as described interactions within these niches and with the surrounding infiltrating immune cells of the TME. By linking patient characteristics with the heterogeneous immune composition we are building an immune stratification that can be linked to patient survival in GBM. Conclusion Generating an immune stratification for GBM will allow us to identify immune characteristics responsible for longer or even exceptional survival, as well as thoroughly identify tumor components that may serve as a potential target for personalized treatment strategies. Therefore, this study is also an essential initial step towards such clinical trials which alter the TME in a favorable way with a personalized modulation strategy.

ATRA works synergistically with the γ-secretase inhibitor crenigacestat to augment BCMA on multiple myeloma and the efficacy of BCMA-CAR T-cells.

B-cell maturation antigen (BCMA) is the lead antigen for CAR T-cell therapy in multiple myeloma (MM). A challenge is inter- and intra-patient heterogeneity in BCMA expression on MM cells and BCMA downmodulation under therapeutic pressure. Accordingly, there is a desire to augment and sustain BCMA expression on MM cells in patients that receive BCMA-CAR T-cell therapy. We used all-trans retinoic acid (ATRA) to augment BCMA expression on MM cells and to increase the efficacy of BCMA-CAR T-cells in pre-clinical models. We show that ATRA treatment leads to an increase in BCMA transcripts by quantitative PCR and an increase in BCMA protein expression by flow cytometry in MM cell lines and primary MM cells. Analyses with super-resolution microscopy confirmed increased BCMA protein expression and revealed an even distribution of non-clustered BCMA molecules on the MM cell membrane after ATRA treatment. The enhanced BCMA expression on MM cells after ATRA treatment led to enhanced cytolysis, cytokine secretion and proliferation of BCMA-CAR T-cells in vitro, and increased efficacy of BCMA-CAR T-cell therapy in a murine xenograft model of MM in vivo (NSG/MM1.S). Combination treatment of MM cells with ATRA and the γ-secretase inhibitor crenigacestat further enhanced BCMA expression and the efficacy of BCMA-CAR T-cell therapy in vitro and in vivo. Taken together, the data show that ATRA treatment leads to enhanced BCMA expression on MM cells and consecutively, enhanced reactivity of BCMA-CAR T-cells. The data support the clinical evaluation of ATRA in combination with BCMA-CAR T-cell therapy and potentially, other BCMA-directed immunotherapies.

All-trans retinoic acid works synergistically with the γ-secretase inhibitor crenigacestat to augment BCMA on multiple myeloma and the efficacy of BCMA-CAR T cells.

B-cell maturation antigen (BCMA) is the lead antigen for chimeric antigen receptor (CAR) T-cell therapy in multiple myeloma (MM). A challenge is inter- and intra-patient heterogeneity in BCMA expression on MM cells and BCMA downmodulation under therapeutic pressure. Accordingly, there is a desire to augment and sustain BCMA expression on MM cells in patients that receive BCMA-CAR T-cell therapy. We used all-trans retinoic acid (ATRA) to augment BCMA expression on MM cells and to increase the efficacy of BCMA-CAR T cells in pre-clinical models. We show that ATRA treatment leads to an increase in BCMA transcripts by quantitative reverse transcription polymerase chain reaction and an increase in BCMA protein expression by flow cytometry in MM cell lines and primary MM cells. Analyses with super-resolution microscopy confirmed increased BCMA protein expression and revealed an even distribution of non-clustered BCMA molecules on the MM cell membrane after ATRA treatment. The enhanced BCMA expression on MM cells after ATRA treatment led to enhanced cytolysis, cytokine secretion and proliferation of BCMA-CAR T cells in vitro, and increased efficacy of BCMA-CAR T-cell therapy in a murine xenograft model of MM in vivo (NSG/MM.1S). Combination treatment of MM cells with ATRA and the γ- secretase inhibitor crenigacestat further enhanced BCMA expression and the efficacy of BCMA-CAR T-cell therapy in vitro and in vivo. Taken together, the data show that ATRA treatment leads to enhanced BCMA expression on MM cells and consecutively, enhanced reactivity of BCMA-CAR T cells. The data support the clinical evaluation of ATRA in combination with BCMA-CAR T-cell therapy and potentially, other BCMA-directed immunotherapies.

Dualistic classification of high grade serous ovarian carcinoma has its root in spatial heterogeneity

IntroductionWidespread intra-peritoneal metastases is a main feature of high grade serous ovarian carcinoma (HGSOC). Recently, the extent of tumour heterogeneity was used to evaluate the cancer genomes among multi-regions in HGSOC. However, there is no consensus on the effect of tumour heterogeneity on the evolution of the tumour metastasis process in HGSOC. ObjectivesWe performed whole-exome sequencing in multiple regions of matched primary and metastatic HGSOC specimens to reveal the genetic mechanisms of ovarian tumourigenesis and malignant progression. Methods63 samples (including ovarian carcinoma, omentum metastasis, and normal tissues) were used. We analyzed the genomic heterogeneity, traced the subclone dissemination and establishment history and compared the different genetic characters of cancer evolutionary models in HGSOC. ResultsWe found that HGSOC had substantial intra-tumour heterogeneity (median 54.2, range 0 ∼ 106.7), high inter-patient heterogeneity (P < 0.001), but relatively limited intra-patient heterogeneity (P = 0.949). Two COSMIC mutational signatures were identified in HGSOCs: signature 3 was related to homologous recombination, and signature 1 was associated with aging. Two scenarios were identified by phylogenetic reconstruction in our study: 3 cases (33.3 %) showed star topology, and the other 6 cases (66.7 %) displayed tree topology. Compared with star topology group, more driver events were identified in tree topology group (P < 0.001), and occurred more frequently in early stage than in late stage of clonal evolution (P < 0.001). Moreover, compared with the star topology group, the tree topology group showed higher rate of intra-tumour heterogeneity (P = 0.045). ConclusionA dualistic classification model was proposed for the classification of HGSOC based on spatial heterogeneity, which may contribute to better managing patients and providing individual treatment for HGSOC patients.

A pipeline for copy number profiling of single circulating tumour cells to assess intrapatient tumour heterogeneity.

Intrapatient tumour heterogeneity is likely a major determinant of clinical outcome in cancer patients. To assess heterogeneity in a minimally invasive manner, methods to perform single circulating tumour cell (CTC) genomics at high resolution are necessary. However, due to the rarity of CTCs, development of such methods is challenging. Here, we developed a modular single CTC analysis pipeline to assess intrapatient heterogeneity by copy number (CN) profiling. To optimize this pipeline, spike‐in experiments using MCF‐7 breast cancer cells were performed. The VyCAP puncher system was used to isolate single cells. The quality of whole genome amplification (WGA) products generated by REPLI‐g and Ampli1™ methods, as well as the results from the Illumina Truseq and the Ampli1™ LowPass library preparation techniques, was compared. Moreover, a bioinformatic pipeline was designed to generate CN profiles from single CTCs. The optimal combination of Ampli1™ WGA and Illumina Truseq library preparation was successfully validated on patient‐derived CTCs. In conclusion, we developed a novel modular pipeline to isolate single CTCs and subsequently generate detailed patient‐derived CN profiles that allow assessment of intrapatient heterogeneity in future studies.

Delineating the intra-patient heterogeneity of molecular alterations in treatment-naïve colorectal cancer with peritoneal carcinomatosis

AbstractIn a non-negligible number of patients with metastatic colorectal cancer (mCRC), the peritoneum is the predominant site of dissemination. Cure can be achieved by cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC), but this procedure is associated with long-term morbidity and high relapse rates. Thus, there is a pressing need for improved therapeutic strategies and complementary biomarkers. The present study explored the molecular heterogeneity in mCRC with peritoneal carcinomatosis (PC), and the potential clinical implications thereof. Multi-region immunohistochemical profiling and deep targeted DNA-sequencing was performed on chemotherapy-naïve tumours from seven patients with synchronous colorectal PC who underwent CRS and HIPEC. In total, 88 samples (5-19 per patient) were analysed, representing primary tumour, lymph node metastases, tumour deposits, PC and liver metastases. Expression of special AT-rich sequence-binding protein 2 (SATB2), a marker of colorectal lineage, was lacking in the majority of cases, and a conspicuous intra-patient heterogeneity was denoted for expression of the proposed prognostic and predictive biomarker RNA-binding motif protein 3 (RBM3). Loss of mismatch repair proteins MLH1 and PSM2, observed in one case, was concordant with microsatellite instability and the highest tumour mutational burden. When present in a patient, mutations in key CRC driver genes, i.e., KRAS, APC and TP53, were homogenously distributed across all samples, while less common mutations were more heterogenous. On the same note, copy number variations showed intra-patient as well inter-patient heterogeneity. In two out of seven cases, hierarchical clustering revealed that samples from the PC and lymph node metastases were more similar to each other than to the primary tumour. In summary, these findings should encourage additional studies addressing the potential distinctiveness of mCRC with PC, which might pave the way for improved personalized treatment of these patients.

Abstract 611: Assessment of tumor mutation burden and microsatellite instability by single-cell circulating tumor cell genomic profiling

Abstract The success of immune checkpoint inhibitors rests on biomarkers such as tumor mutation burden (TMB) and microsatellite instability (MSI), both FDA-approved predictors of anti PD-1/L1 therapy benefit. Tissue biopsies often collected once in the metastatic setting through an invasive procedure, or archived primary tumor tissue often collected much prior to treatment consideration, are the specimen types of choice for biomarker identification. The tissue sample originates from a limited region of one disease site, which may limit its usefulness given intra-patient tumor heterogeneity. TMB and MSI measurement by liquid biopsy, including proteins, circulating tumor cells (CTC), and cell-free circulating tumor DNA (ctDNA), is an attractive, minimally-invasive way to obtain a real-time picture of the entire disease. While TMB and MSI assessment from ctDNA have been reported, their measurement can be limited by low ctDNA tumor fraction. Single-cell next generation sequencing of CTC, on the other hand, is a particularly well-suited, but largely unexplored method of measuring TMB and MSI to complement tissue and ctDNA for better overall specificity of detection. In this proof-of-concept study, we show the ability to detect single-cell TMB and MSI. We analyzed 14 CTC and 4 ctDNA samples from 6 metastatic breast cancer patients, as well as 3 single cells and 1 cell pellet sample each from HCT-116 (MSI-High) and WiDr (MSI-Low) cell lines. CTC and cell line cells were enriched with the CellSearch® system and/or isolated with the DEPArray™ system. Whole genome amplified single-cell DNA was sequenced with the Oncomine Comprehensive Assay covering ~500 genes and 1.1Mb of genomic space. TMB and MSI scores obtained in CTC and ctDNA were compared to those measured in matched clinical tissue biopsies. Single-cell TMB scores and MSI status were assessable in all CTC tested. CTC TMB scores were highly concordant with the matched tissue samples (r=1.00), as were ctDNA TMB scores (r=0.98) in patients with assessable TMB scores in both biospecimen types compared. Importantly, TMB was detectable in CTC from one patient whose tissue sample was inadequate for clinical sequencing, and from another patient with inadequate, low tumor fraction ctDNA. Intriguingly, one patient harbored 3 TMB-high and 2 TMB-low CTC, potentially indicating intra-patient TMB heterogeneity. The known MSI-low status from clinical tumor tissue sequencing was correctly detected in CTC and ctDNA from all patients. MSI status and scores from single cells of HCT-116 and WiDr cell lines purified with the DEPArray™ system (mimicking CTC isolation), perfectly matched that of the corresponding cell pellet samples (r=1.00). Taken together, these data suggest the potential validity and continued interrogation of potential utility of CTC TMB and MSI detection to complement tissue and ctDNA in guiding checkpoint inhibitor immunotherapy. Citation Format: Andi K. Cani, Emily M. Dolce, Chia-Jen Liu, Brittany Rupp, Elizabeth P. Darga, Costanza Paoletti, Dafydd G. Thomas, Yi-Mi Wu, Dan R. Robinson, Sunitha Nagrath, Arul M. Chinnaiyan, Scott A. Tomlins, Aaron M. Udager, John M. Carethers, Erin F. Cobain, Daniel F. Hayes. Assessment of tumor mutation burden and microsatellite instability by single-cell circulating tumor cell genomic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 611.

Abstract 1700: Serial monitoring of single-cell circulating tumor cell genomics in metastatic lobular breast cancer to identify precision and immuno-oncology biomarkers with therapeutic implications

Abstract Clinical decisions for precision and immuno-oncology therapies are based on predictive biomarkers commonly obtained from a single metastatic biopsy, or from archived primary tumor material. Circulating genomic biomarkers present a minimally invasive way to monitor the intra-patient tumor heterogeneity and its fluctuations in order to provide a real-time evaluation of the changing clonal architecture with potential therapeutic implications. Single-cell DNA next generation sequencing (scNGS) of circulating tumor cells (CTC) is a particularly well-suited method of unraveling and monitoring that heterogeneity to complement biomarker information obtained from tissue and cell-free circulating tumor DNA (ctDNA). In this proof-of-concept study we analyzed 123 CTC, 15 white blood cells (WBC), and ctDNA from 15 CTC-positive lobular breast cancer patients, five of whom had CTC available at both metastatic baseline and after progression on a variety of therapies chosen at their physician’s discretion. CTC were enriched with the CellSearch® system and isolated as single cells with the DEPArray™ system. Whole genome amplified CTC DNA underwent scNGS with the Oncomine Comprehensive Assay covering ~500 genes and 1.1Mb of genomic space to detect mutations, copy number alterations, tumor mutation burden (TMB) and microsatellite instability (MSI). 99.1% of cells were informative, with a mean sequencing depth of 664x. Using our previously developed, CTC-based precision medicine reporting platform, MI-CTCSeq, multiple CTC in seven of 15 patients (47%) had mutations that were actionable by FDA-approved targeted therapies including in the oncogenes PIK3CA (alpelisib) and FGFR2 (erdafitinib). 13 patients (87%) displayed intra-patient, inter-CTC genomic heterogeneity of putative driver mutations. Two of five (40%) patients with CTC at both baseline and progression displayed fluctuations in their CTC subclonal makeup between timepoints. One of the two harbored a baseline ESR1 (estrogen receptor α) p.D538G activating mutation that largely disappeared at progression and was replaced by a CTC subclone with a different ESR1 activating mutation, p.Y537S. Intriguingly, this patient’s CTC also harbored an FGFR2 p.K659M mutation in an actionable “hotspot” at progression, which was absent at baseline, suggesting potential utility of serial monitoring by CTC scNGS. TMB scores and MSI status in CTC were highly concordant with those measured in clinical tissue biopsies. Taken together, these data suggest the non-invasive interrogation of the CTC genomic landscape and its serial monitoring to inform precision and immuno-oncology treatments in real time. Citation Format: Andi K. Cani, Emily M. Dolce, Elizabeth P. Darga, Kevin Hu, Chia-Jen Liu, James M. Rae, Daffyd G. Thomas, Scott A. Tomlins, Arul M. Chinnaiyan, Aaron M. Udager, Costanza Paoletti, Erin F. Cobain, Daniel F. Hayes. Serial monitoring of single-cell circulating tumor cell genomics in metastatic lobular breast cancer to identify precision and immuno-oncology biomarkers with therapeutic implications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1700.

Abstract 1957: Dissecting CTC phenotypic heterogeneity for predictive biomarker identification and its association with clonal lineage through single-cell multi-omic profiling

Abstract Background: The mutation, selection, and adaptation of tumor cells along disease progression exhibits a spectrum of phenotypic and genotypic heterogeneity. The importance of distinguishing phenotypic states of CTC in addition to genomic alterations has been addressed for identifying predictive biomarkers and understanding CTC biology. Current liquid biopsy usually relies on only one phenotypic state of CTCs without further genomic validation of cancer cell identity. Here, we developed HDSCA3.0, a multi-omic platform, which could distinguish various phenotypic states of CTCs followed by genomic characterization. Methods: Paired peripheral blood (PB) and bone marrow aspirate (BMA) samples were collected prospectively from 80 metastatic castrate resistant prostate cancer (mCRPC) patients for retrospective analysis. Seventy-nine of them were part of Cabazitaxel With or Without Carboplatin Trial (NCT01505868) and one independent index patient was included with aggressive disease and unfavorable prognosis. CTCs were detected, classified, enumerated through a four-channel immunostaining assay (DAPI|Cytokeratin|Vimentin|CD45/CD31) and a computational pipeline followed by manual curation, and subjected to single-cell copy-number profiling for clonality analysis and aggressive variant prostate cancer molecular signature (AVPC-MS) detection i.e. 2+ defects in PTEN, RB1, and TP53 genes. Results: CTC subtypes were categorized from Cytokeratin-positive rare cell groups based on the presence of mesenchymal features and platelet attachment. Of 79 trial cases, 77 (97.5%) had CTCs, 24 (30.4%) were positive for platelet-coated CTCs (pc.CTCs) and 25 (38.5%) of 65 sequenced patients exhibited AVPC-MS in CTCs. Survival analysis indicated that the presence of pc.CTCs identified the subset of patients who were AVPC-MS-positive with the worst prognosis. In AVPC-MS-negative patients, its presence showed significant survival improvement from combination therapy. In index patient, we uniquely identified genetically clonal mesenchymal-like CTCs (mes.CTCs) and their presence was significantly associated with one subclone emerged along clonal lineage. Meanwhile, differences of CTC abundance and phenotypic diversity were observed between paired PB and BMA as well as genomic variations. Conclusion: Our findings suggest pc.CTCs and AVPC-MS in CTCs as a multi-omic predictive biomarker to stratify mCRPC subpopulations with the worst prognosis and the most significant benefit of additional platinum therapy and illustrate a robust approach to analyze intra-patient CTC genotypic and phenotypic heterogeneity and association. Citation Format: Shoujie Chai, Nicholas Matsumoto, Ryan Storgard, Chen-Ching Peng, Ana Aparicio, Benjamin Ormseth, Kate Rappard, Cunningham Kate, Anand Kolatkar, Rafael Nevarez, Kai Han Tu, Ching-Ju Hsu, Amin Naghdloo, Paymaneh Malihi, Liya Xu, Paul Corn, Amado Zurita-Saavedra, James Hicks, Carmen Ruiz-Velasco, Peter Kuhn. Dissecting CTC phenotypic heterogeneity for predictive biomarker identification and its association with clonal lineage through single-cell multi-omic profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1957.

Abstract LB565: Efficacy of a highly potent and selective KIT V654A inhibitor for treatment of imatinib resistant GIST

Abstract Gastrointestinal stromal tumor (GIST) is the most common type of sarcoma, with approximately 5,000 patients diagnosed per year in the US. Approximately 80% of patients with GIST present with mutations in the c-KIT oncogene at exon 9 or 11, which leads to constitutive, ligand-independent activation of the KIT receptor tyrosine kinase. For patients with metastatic GIST, frontline therapy with imatinib is effective, with a response rate of approximately 51-54% and median progression-free survival (PFS) of 19-23 months, in a molecularly unselected population. Other agents are approved for advanced GIST, without molecular selection, after progression on imatinib, including sunitinib, regorafenib, and ripretinib; however, response rates are less than 10% with PFS of approximately 5-6 months. Notably, patients who progress on imatinib and other tyrosine kinase inhibitors may develop a variety of on-target resistance mutations in the KIT oncogene, such as those in exon 17 (including at amino acids D816 and D820, activation loop mutation), exon 13 (V654A, ATP-binding region mutation), and less frequently in exon 14 (T670I, gatekeeper mutation). Several KIT inhibitors have been developed to potently target the exon 17 resistance mutations (avapritinib and ripretinib); however, there remains an important medical need in 2nd- and 3rd-line therapy in a molecularly unselected population of imatinib-resistant GIST. This suggests more broad-spectrum KIT inhibition is likely required, a hypothesis supported by the observation of large inter- and intra-patient heterogeneity of KIT secondary mutations across hundreds of samples obtained from patients with GIST treated with avapritinib. Sequencing data from the NAVIGATOR phase 1 trial (NCT02508532) revealed that patients with KIT mutant GIST and with the KIT V654A secondary resistance mutation had a poor response to treatment with avapritinib. To address this, we developed a highly potent and selective inhibitor of KIT V654A. This inhibitor showed dose-dependent modulation of downstream pharmacodynamic markers and induced tumor regression in a mastocytoma xenograft model driven by an exon 11 plus 13 V654A resistance mutation. Importantly, this inhibitor was generally well-tolerated and showed high selectivity over wild-type KIT. These findings suggest this novel KIT inhibitor has the potential to be used as a single agent or combination therapy for patients with imatinib-resistant GIST harboring the KIT V654A mutation. Citation Format: Alexandra R. Grassian, Joseph Kim, Omar Ahmad, Kevin Barvian, Alison Davis, Tom Dineen, Wei Hu, Ebby Job, Ludivine Moine, Kate Newberry, Maria Roche, Doug Shorten, Yeon Sook Choi, Francis Wolenski, Sebastian Bauer, Cesar Serrano, Jonathan Trent, Suzanne George. Efficacy of a highly potent and selective KIT V654A inhibitor for treatment of imatinib resistant GIST [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB565.

Multitarget Molecular Imaging in Metastatic Castration Resistant Adenocarcinoma Prostate Cancer with Therapy Induced Neuroendocrine Differentiation.

Neuroendocrine differentiation of prostate cancer (NEDPC) includes de novo presentation and secondary to epigenetic changes, referred as therapy-induced neuroendocrine prostate cancer (t-NEPC). Molecular imaging with prostate-specific membrane antigen (PSMA) and somatostatin analogues positron emission tomography (PET/CT) in NEDPC have not been validated. 18F-FDG (fluorodeoxyglucose) PET/CT has numerous limitations in prostate cancer (PCa) and the utility in NEDPC has only been reported in a few series of cases. The objective of this study is to compare the lesions detection rate of the three radiotracers in metastatic t-NEPC patients. (1) Material and Methods: Retrospective evaluation of patients with prostate adenocarcinoma treated with androgen deprivation therapy, chemotherapy, a novel androgen receptor pathway inhibitor or a combination of them and a second tumour biopsy confirming t-NEPC was made. All patients underwent 18F PSMA-1007, 18F AlF-NOTA-Octreotide, and 18F-FDG PET/CT. Evaluation of positive lesions was determined and SUVmax of each radiotracer was estimated and correlated with computer tomography (CT) findings. (2) Results: A total of eight patients were included. The mean time from diagnosis of prostate adenocarcinoma to t-NEPC was 28.2 months, with a mean serum specific prostate antigen (PSA) of 16.6 ng/dl at the time of NEPC diagnosis. All patients were treated with antiandrogen therapy and 87.5% with chemotherapy. A total of 273 lesions were identified by CT from which 182 were detected by 18F-FDG PET/CT, 174 lesions by 18F PSMA-1007, and 59 by 18F AlF-NOTA-Octreotide. An interpatient analysis of the lesions was performed and dual tracer 18F-FDG PET/CT and 18F PSMA-1007 PET/CT detected a total of 270/273 lesions (98.9%). (3) Conclusions: NEDPC patients demonstrated wide inter and intrapatient molecular imaging heterogeneity within the three radiotracers. 18F-FDG detected most lesions in t-NEPC among all radiotracers, especially in visceral sites; 18F PSMA-1007 detected more bone lesions. 18F AlF-NOTA-Octreotide showed no significant utility.

Incorporation of intrapatient response heterogeneity using 18F-NaF PET/CT imaging improves outcome prediction models for metastatic prostate cancer patients.

e13554 Background: Quantitative 18F-NaF PET/CT imaging metrics have been shown to be prognostic in metastatic prostate cancer (mPC) patients. However, previous studies have shown conflicting results in which metrics could be prognostic. This study investigates if current methods from literature generalize to external datasets and explores which combination of features are necessary to for survival models to generalize across datasets. Methods: Imaging and progression-free survival (PFS) data from 118 patients with mPC from four separate prospective clinical trials were gathered retrospectively. Patients received 18F-NaF PET/CT imaging at baseline and at follow-up, between eight and thirteen weeks. TRAQinform IQ technology (AIQ Solutions) was used to identify, segment, and track individual lesions from baseline to follow-up. Eighty-four imaging features were extracted from each patient and sorted into baseline, follow-up, response, patient-level (no inter-lesion comparison), and intrapatient heterogeneity (comparisons between lesions). The data was split into two training and testing sets, 44 patients from one study and 73 patients from the remaining 3 studies. As they can utilize large number of inputs without overfitting, random survival forest (RSF) models were chosen to evaluate performance of feature sets in predicting PFS. Different combinations of features were used as inputs to RSF models to compare single timepoint features with response features and patient-level features with intrapatient heterogeneity features. The performance of the RSF models, together with other methods identified in literature, were evaluated in each dataset using Kaplan-Meier analysis for categorical variables and the c-index for continuous variables. Results: No patient-level imaging features highlighted by literature displayed significant association to PFS across all four clinical trials (c-index &lt; 0.62 in at least one dataset). Other criteria from literature did not generalize across all datasets (P &gt; 0.05). The RSF model trained with all features had high c-indices in all four datasets (range: 0.66-0.80). RSF models built with response features (min: 0.63) performed better on average than models built with features obtained from single timepoints (min: 0.55). Patient-level features (min: 0.56) were not sufficient in all testing scenarios as compared to intrapatient heterogeneity features (min: 0.63). Conclusions: The candidate imaging biomarkers from previous 18F-NaF PET/CT imaging studies of mPC patients did not generalize across all datasets. Incorporating response and heterogeneity features with single-timepoint and patient-level features resulted in RSF prediction models which were generalizable across all datasets. Use of such models hold promise for improving outcome prediction in mPC patients.