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The interaction between neoplastic and stromal cells within a tumor mass plays an important role in cancer biology. However, it is challenging to distinguish between tumor and stromal cells in mesenchymal tumors because lineage-specific cell surface markers typically used in other cancers do not distinguish between the different cell subpopulations. Desmoid tumors consist of mesenchymal fibroblast-like cells driven by mutations stabilizing beta-catenin. Here we aimed to identify surface markers that can distinguish mutant cells from stromal cells to study tumor–stroma interactions. We analyzed colonies derived from single cells from human desmoid tumors using a high-throughput surface antigen screen, to characterize the mutant and nonmutant cells. We found that CD142 is highly expressed by the mutant cell populations and correlates with beta-catenin activity. CD142-based cell sorting isolated the mutant population from heterogeneous samples, including one where no mutation was previously detected by traditional Sanger sequencing. We then studied the secretome of mutant and nonmutant fibroblastic cells. PTX3 is one stroma-derived secreted factor that increases mutant cell proliferation via STAT6 activation. These data demonstrate a sensitive method to quantify and distinguish neoplastic from stromal cells in mesenchymal tumors. It identifies proteins secreted by nonmutant cells that regulate mutant cell proliferation that could be therapeutically. Significance: Distinguishing between neoplastic (tumor) and non-neoplastic (stromal) cells within mesenchymal tumors is particularly challenging, because lineage-specific cell surface markers typically used in other cancers do not differentiate between the different cell subpopulations. Here, we developed a strategy combining clonal expansion with surface proteome profiling to identify markers for quantifying and isolating mutant and nonmutant cell subpopulations in desmoid tumors, and to study their interactions via soluble factors.

Background: Metastasis is the leading cause of cancer related deaths in breast cancer patients. Lymphovascular invasion represents one of the earliest stages of metastasis wherein the cells are introduced to a very different and distinct microenvironment. Methods: We leveraged spatial techniques developed for limited specimens in archival tissue to study patient matched cross-sectional tumor samples from different stages of breast neoplasia including normal breast, ductal carcinoma in situ (DCIS), primary invasive carcinoma (IBC), lymphovascular invasion (LVI) and regional lymph node metastasis. We selected a set of 21 patients with ER+ breast cancer to generate cross-sectional samples of each of these stages, for a total of 331 samples. The areas of LVI were identified by a combination of H&E review and immunohistochemistry for podoplanin. We performed smart-3SEQ for gene expression profiling and light pass whole genome sequencing for DNA copy number alterations. Results: We profiled the spectrum of neoplasia for transcriptome-wide gene expression. Principal component analysis of all 252 DCIS, LVI, IBC, or metastasis samples using the top 500 genes with the highest variance demonstrated that clustering was roughly based on the diagnostic stage (i.e. DCIS, LVI, IBC, or metastasis). Differential gene expression profiling identified thousands of genes increased or decreased in expression across the transitional stages with the largest change in gene expression being the transition from normal breast to DCIS, dominated by gene expression down regulation. We next performed NMF clustering on 62 samples of LVI from 18 cases and identified two patterns of gene expression which define two subgroups. Gene ontology analysis revealed that one cluster was associated with increased proliferation and metabolism, whereas the second cluster was dominated by an immune response. When we analyzed the immune and proliferative LVI subgroups separately, we found that the immune profiles in the patient matched IBC and LVI samples from the LVI Immune cluster were similar, whereas the immune profiles in the patient matched IBC and LVI samples from the Proliferative cluster were significantly different. At the LVI stage, all immune cell populations estimated by CibersortX were decreased in the Proliferative LVI cluster. These changes were validated using immunofluorescence for proliferation (Ki67), T cells (CD3) and macrophages (CD68) on the same samples. Using the LVI centroids, we built a model that could predict the same clusters in the METABRIC IBC. Kaplan-Meier analysis showed a significant difference between groups, with the Proliferative-like IBC group having a worse prognosis than the Immune-like IBC group. Conclusions: We observed a dichotomy at the LVI stage with a more proliferative cluster that may escape the immune response and an immune cluster which has a microenvironment with a similar pattern to its primary IBC. The recognition of two groups of LVI, differing in immune association and proliferation, raises the possibility that the risk of metastasis could be different in these two groups, leading to different biological pathways of progression. Citation Format: Belén Rivero-Gutiérrez, Diego Mallo, Almudena Espín-Pérez, Sujay Vennam, Chunfang Zhu, Sushama Varma, Greg Scott, Joseph Foley, E Shelley Hwang, Carlo Maley, Robert West. Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD2-09.

Purpose: A major component of cells in tenosynovial giant cell tumor (TGCT) consists of bystander macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. An autocrine loop was postulated where the neoplastic cells would be stimulated through CSF1R expressed on their surface. Here, we use single-cell RNA sequencing (scRNA-seq) to investigate cellular interactions in TGCT. Experimental Design: A total of 18,788 single cells from three TGCT and two giant cell tumor of bone (GCTB) samples underwent scRNA-seq. The three TGCTs were additionally analyzed using long-read RNA sequencing. Immunofluorescence and IHC for a range of markers were used to validate and extend the scRNA-seq findings. Results: Two recurrent neoplastic cell populations were identified in TGCT that are highly similar to nonneoplastic synoviocytes. We identified GFPT2 as a marker that highlights the neoplastic cells in TCGT. We show that the neoplastic cells themselves do not express CSF1R. We identified overlapping MAB features between the giant cells in TGCT and GCTB. Conclusions: The neoplastic cells in TGCT are highly similar to nonneoplastic synoviocytes. The lack of CSF1R on the neoplastic cells indicates they may be unaffected by current therapies. High expression of GFPT2 in the neoplastic cells is associated with activation of the YAP1/TAZ pathway. In addition, we identified expression of the platelet-derived growth factor receptor in the neoplastic cells. These findings suggest two additional pathways to target in this tumor.

Decreasing mutational frequency with increasing passages in a desmoid tumor primary culture.

The interaction between neoplastic and stromal cells within a tumor mass plays an important role in cancer biology. However, it is challenging to distinguish between tumor and stromal cells in mesenchymal tumors because lineage-specific cell surface markers typically used in other cancers do not distinguish between the different cell subpopulations. Desmoid tumors consist of mesenchymal fibroblast-like cells driven by mutations stabilizing beta-catenin. Here we aimed to identify surface markers that can distinguish mutant cells from stromal cells to study tumor–stroma interactions. We analyzed colonies derived from single cells from human desmoid tumors using a high-throughput surface antigen screen, to characterize the mutant and nonmutant cells. We found that CD142 is highly expressed by the mutant cell populations and correlates with beta-catenin activity. CD142-based cell sorting isolated the mutant population from heterogeneous samples, including one where no mutation was previously detected by traditional Sanger sequencing. We then studied the secretome of mutant and nonmutant fibroblastic cells. PTX3 is one stroma-derived secreted factor that increases mutant cell proliferation via STAT6 activation. These data demonstrate a sensitive method to quantify and distinguish neoplastic from stromal cells in mesenchymal tumors. It identifies proteins secreted by nonmutant cells that regulate mutant cell proliferation that could be therapeutically.Significance:Distinguishing between neoplastic (tumor) and non-neoplastic (stromal) cells within mesenchymal tumors is particularly challenging, because lineage-specific cell surface markers typically used in other cancers do not differentiate between the different cell subpopulations. Here, we developed a strategy combining clonal expansion with surface proteome profiling to identify markers for quantifying and isolating mutant and nonmutant cell subpopulations in desmoid tumors, and to study their interactions via soluble factors.

Type B (mutant) cells exhibit higher alpha-smooth muscle actin levels at the protein and RNA level.

Densitometry of selected secreted proteome from mutant and non-mutant conditioned media

Cell surface profiling data of mutant and non-mutant desmoid tumor-derived colonies. Name of the sample indicates the mutation status (mutant (MUT) or wildtype (WT)) of the pooled colonies and the genotype (T41A or S45F) of the original primary sample.

Summary of double-color cell sorting experiments.

Podoplanin-based flow cytometry of mutant and non-mutant colonies.

Supplementary Figure S1. ALK copy number data from TCGA-FX-A48G and TCGA-IW-A3M6 LMS visualized using IGV (Broad, MIT) Supplementary Table S1. Identification of ALK rearrangements using ChimeraScan algorithm. Supplementary Figure S2. Results from the fusion analysis pipeline run on RNA-seq data for TCGA-FX-A48G identifying KANK2-ALK Supplementary Figure S3. Results from the fusion analysis pipeline run on RNA-seq data for TCGA-IW-A3M6 identifying ACTG2-ALK Supplementary Figure S4. Confirmation of KANK2-ALK transgene expression from transformed Ba/F3 cells. Supplementary Figure S5. Dose-response inhibitor assay with ALK inhibitors with Ba/F3 parental cells in presence of IL-3 Supplementary Figure S6. Body weight of mice treated with vehicle, crizotinib or lorlatinib

Supplementary Figure from Interactions in CSF1-Driven Tenosynovial Giant Cell Tumors

Supplementary Table from Interactions in CSF1-Driven Tenosynovial Giant Cell Tumors

Purpose:A major component of cells in tenosynovial giant cell tumor (TGCT) consists of bystander macrophages responding to CSF1 that is overproduced by a small number of neoplastic cells with a chromosomal translocation involving the CSF1 gene. An autocrine loop was postulated where the neoplastic cells would be stimulated through CSF1R expressed on their surface. Here, we use single-cell RNA sequencing (scRNA-seq) to investigate cellular interactions in TGCT.Experimental Design:A total of 18,788 single cells from three TGCT and two giant cell tumor of bone (GCTB) samples underwent scRNA-seq. The three TGCTs were additionally analyzed using long-read RNA sequencing. Immunofluorescence and IHC for a range of markers were used to validate and extend the scRNA-seq findings.Results:Two recurrent neoplastic cell populations were identified in TGCT that are highly similar to nonneoplastic synoviocytes. We identified GFPT2 as a marker that highlights the neoplastic cells in TCGT. We show that the neoplastic cells themselves do not express CSF1R. We identified overlapping MAB features between the giant cells in TGCT and GCTB.Conclusions:The neoplastic cells in TGCT are highly similar to nonneoplastic synoviocytes. The lack of CSF1R on the neoplastic cells indicates they may be unaffected by current therapies. High expression of GFPT2 in the neoplastic cells is associated with activation of the YAP1/TAZ pathway. In addition, we identified expression of the platelet-derived growth factor receptor in the neoplastic cells. These findings suggest two additional pathways to target in this tumor.

Supplementary Tables S1-S9. Table S1: Clinicopathological characterization of 99 Leiomyosarcoma cases; Table S2: Patient clinical features for TCGA dataset (N=82); Table S3: The number of overlapping genes by SAMSeq analysis between 3SEQ and TCGA RNASEQ datasets; Table S4: Comparison of expression profiles between TCGA subtypes with SAMSeq; Table S5: SAMSeq results between different LMS subtypes in 3SEQ data; Table S6: Enriched GO biological processes (BP) terms by genes over-expressed in each LMS subtype; Table S7: IHC scoring results for protein LMOD1 and ARL4C on LMS cases analysed by 3SEQ; Table S8: Univariate and multivariate analysis of different subtypes of LMS defined by IHC staining and other factors; Table S9: Patient characteristics on TA�201 (N=127).

Purpose: The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA.Experimental Design: We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma.Results: We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles.Conclusions: Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. Clin Cancer Res; 24(11); 2688–99. ©2018 AACR.

Purpose: Macrophages play an important role in breast carcinogenesis. The pathways that mediate the macrophage contribution to breast cancer and the heterogeneity that exists within macrophages are incompletely understood. Macrophage colony-stimulating factor 1 (CSF1) is the primary regulator of tissue macrophages. The purpose of this study was to define a novel CSF1 response signature and to evaluate its clinical and biological significance in breast cancer.Experimental Design: We defined the CSF1 response signature by identifying genes overexpressed in tenosynovial giant cell tumor and pigmented villonodular synovitis (tumors composed predominantly of macrophages recruited in response to the overexpression of CSF1) compared with desmoid-type fibromatosis and solitary fibrous tumor. To characterize the CSF1 response signature in breast cancer, we analyzed the expression of CSF1 response signature genes in eight published breast cancer gene expression data sets (n = 982) and did immunohistochemistry and in situ hybridization for CSF1 response genes on a breast cancer tissue microarray (n = 283).Results: In both the gene microarray and tissue microarray analyses, a consistent subset (17-25%) of breast cancers shows the CSF1 response signature. The signature is associated with higher tumor grade, decreased expression of estrogen receptor, decreased expression of progesterone receptor, and increased TP53 mutations (P < 0.001).Conclusions: Our data show that the CSF1 response signature is consistently seen in a subset of breast carcinomas and correlates with biological features of the tumor. Our findings provide insight into macrophage biology and may facilitate the development of personalized therapy for patients most likely to benefit from CSF1-targeted treatments.

Supplementary Figures S1-S5. Fig. S1: Implication of assuming 4 subtypes of LMS; Fig. S2: Unsupervised hierarchical clustering of core LMS cases with leiomyoma, myometrium and UPS; Fig. S3: Heatmap of IHC staining results of LMOD1 on TA-201 with five other subtype I markers reported previously; Fig. S4: Correlation between reactivity for subtype-specific IHC markers (IHC, x-axis) and mRNA expression levels (TPM, y axis) for all LMS cases; Fig. S5: Correlation of three molecular subtypes based on IHC with outcome.

Purpose: Leiomyosarcoma is a malignant neoplasm with smooth muscle differentiation. Little is known about its molecular heterogeneity and no targeted therapy currently exists for leiomyosarcoma. Recognition of different molecular subtypes is necessary to evaluate novel therapeutic options. In a previous study on 51 leiomyosarcomas, we identified three molecular subtypes in leiomyosarcoma. The current study was performed to determine whether the existence of these subtypes could be confirmed in independent cohorts.Experimental Design: Ninety-nine cases of leiomyosarcoma were expression profiled with 3′end RNA-Sequencing (3SEQ). Consensus clustering was conducted to determine the optimal number of subtypes.Results: We identified 3 leiomyosarcoma molecular subtypes and confirmed this finding by analyzing publically available data on 82 leiomyosarcoma from The Cancer Genome Atlas (TCGA). We identified two new formalin-fixed, paraffin-embedded tissue-compatible diagnostic immunohistochemical markers; LMOD1 for subtype I leiomyosarcoma and ARL4C for subtype II leiomyosarcoma. A leiomyosarcoma tissue microarray with known clinical outcome was used to show that subtype I leiomyosarcoma is associated with good outcome in extrauterine leiomyosarcoma while subtype II leiomyosarcoma is associated with poor prognosis in both uterine and extrauterine leiomyosarcoma. The leiomyosarcoma subtypes showed significant differences in expression levels for genes for which novel targeted therapies are being developed, suggesting that leiomyosarcoma subtypes may respond differentially to these targeted therapies.Conclusions: We confirm the existence of 3 molecular subtypes in leiomyosarcoma using two independent datasets and show that the different molecular subtypes are associated with distinct clinical outcomes. The findings offer an opportunity for treating leiomyosarcoma in a subtype-specific targeted approach. Clin Cancer Res; 21(15); 3501–11. ©2015 AACR.

Supplementary Data from The Macrophage Colony-Stimulating Factor 1 Response Signature in Breast Carcinoma

Supplementary Workbook from The Macrophage Colony-Stimulating Factor 1 Response Signature in Breast Carcinoma

Supplementary Data from Multiomics Analysis of Spatially Distinct Stromal Cells Reveals Tumor-Induced O-Glycosylation of the CDK4–pRB Axis in Fibroblasts at the Invasive Tumor Edge

The invasive leading edge represents a potential gateway for tumor metastasis. The role of fibroblasts from the tumor edge in promoting cancer invasion and metastasis has not been comprehensively elucidated. We hypothesize that cross-talk between tumor and stromal cells within the tumor microenvironment results in activation of key biological pathways depending on their position in the tumor (edge vs. core). Here we highlight phenotypic differences between tumor-adjacent-fibroblasts (TAF) from the invasive edge and tumor core fibroblasts from the tumor core, established from human lung adenocarcinomas. A multiomics approach that includes genomics, proteomics, and O-glycoproteomics was used to characterize cross-talk between TAFs and cancer cells. These analyses showed that O-glycosylation, an essential posttranslational modification resulting from sugar metabolism, alters key biological pathways including the cyclin-dependent kinase 4 (CDK4) and phosphorylated retinoblastoma protein axis in the stroma and indirectly modulates proinvasive features of cancer cells. In summary, the O-glycoproteome represents a new consideration for important biological processes involved in tumor–stroma cross-talk and a potential avenue to improve the anticancer efficacy of CDK4 inhibitors.Significance:A multiomics analysis of spatially distinct fibroblasts establishes the importance of the stromal O-glycoproteome in tumor–stroma interactions at the leading edge and provides potential strategies to improve cancer treatment.See related commentary by De Wever, p. 537

Figure S1 Summary of CAPP-Seq and GRP findings in plasma specimens of 7 LMS patients. Figure S2 Specificity and sensitivity of ctDNA detection by CAPP-Seq in LMS patients. Figure S3 Individual DNA copy number alteration profiles of 22 tumor specimens from 7 LMS patients. CN - copy number Figure S4 UCSC Genome Browser view of genomic region 11q24.3-q25 that was consistently lost across all tumor specimens in patients LMS2, LMS3, LMS4, LMS5 and LMS7. Figure S5 Correlation between ctDNA levels detected by CAPP-Seq (represented as VAF) and GRP (represented as percent of genome altered by copy number alterations). Table S1 Summary of clinical features of 9 LMS patients Table S2 LMS-specific CAPP-Seq selector. Table S3 Tumor specimens used for CAPP-Seq and SNP array analysis. Table S4 Depth of sequencing and % of on-target reads by CAPP-Seq. Table S5 Summary statistics for GRP. Table S6 Input of cfDNA used for CAPP-Seq and GRP. Table S7 Summary of quality control metrics from OncoScan FFPE Assay and the extent of CNAs in 22 LMS tumor specimens.

Measuring gene expression of F3 and PDPN after Wnt3a treatment of skin fibroblasts

Correlation between estimated mutation frequency from Sanger sequencing and percent CD142-positive cells in heterogeneous desmoid tumor samples

Cytokine antibody array to identify differentially secreted factors from isolated mutant and non-mutant cells.

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PDF file - 52K, Clinical information for BCA patient-derived xenografts.

Primers used in real-time quantitative PCR experiments.

Morphological differences in mutant and non-mutant cells isolated by FACS sorting

PDF file - 581K, Breast TICs are enriched in the CD24HiCD49fHi subpopulation (S1); Expression of HER receptors and ligands in breast cancer cell lines (S2); HER2 inhibition reduces the EpCAM- TIC-like subpopulation of SUM149 cells (S3); Breast TICs are enriched in the EPCAM+CD49f+ subpopulation of a triple-negative patient-derived xenograft breast tumor BCA70 (S4); Dual inhibition of HER2 and EGFR targets breast TICs in patient-derived xenograft BCA71 (S5).

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Representative gating strategy

CD142 immunohistochemical analysis in scar tissue cores. Results from duplicate cores per do are shown when available.

Histologic appearance of two cases of desmoid tumors with different patterns of CD142 expression

Co-culturing of mutant desmoid tumor cells with non-mutant fibroblasts increases their proliferation rate

Background. DCIS consists of a molecularly heterogeneous group of premalignant lesions, with variable risk of invasive progression. Understanding biomarkers for invasive progression could help individualize treatment recommendations based upon tumor biology. As part of the NCI Human Tumor Atlas Network (HTAN), we conducted comprehensive genomic analyses on two large DCIS case-control cohorts. Methods. We performed smart3-seq and low-pass whole genome sequencing on two independent, retrospective, longitudinally sampled DCIS case-control cohorts. TBCRC 038 was a multicenter cohort diagnosed with DCIS between 1998 and 2016 at one of the Translational Breast Cancer Research sites; the RAHBT (Resource of Archival Human Breast Tissue) cohort included women identified through the St. Louis Breast Tissue Repository, and the Women’s Health Repository diagnosed between 1997 and 2001. We studied the spectrum of molecular changes present and sought genomic predictors of subsequent ipsilateral breast events (iBEs: DCIS recurrence or invasive progression) in both DCIS epithelium and stroma in formalin fixed paraffin embedded tissue. We generated de novo tumor and stroma-centric subtypes for DCIS that represents fundamental transcriptomic organization. Copy number analysis was performed using low-pass DNA sequencing. Non-negative matrix factorization (NMF) was applied to the RNA expression of all coding genes to identify clusters. A negative-binomial regression model was used to identify differentially expressed genes. Results. We analyzed 677 DCIS samples from 481 patients with 7.1 years median follow-up. In TBCRC samples, we identified three clusters via NMF in TBCRC referred to as ER low, quiescent, and ER high. The ER-low cluster had significantly higher levels of ERBB2 and lower levels of ESR1 compared to quiescent and ER-high clusters. Quiescent cluster lesions were less proliferative and less metabolically active than ER high and ER low subtypes. These findings were replicated in the RAHBT cohort. Focusing on the stromal component of DCIS from laser capture microdissection in RAHBT samples, we identified four distinct DCIS-associated stromal clusters. A “normal-like” stromal cluster with ECM organization and PI3K-AKT signaling; a “collagen-rich” stromal cluster; a “desmoplastic” stromal cluster with high fibroblast and total myeloid abundance, mostly associated with macrophages and myeloid dendritic cells (mDC); and an “immune-dense” stromal cluster. Further, we compared differentially expressed genes in patients with or without subsequent iBEs within 5 years of diagnosis. Hypothesizing that the resulting 812 DE genes (DESeq2) represent multiple routes to subsequent iBEs, we leveraged NMF to identify paths to progression. In both TBCRC and RAHBT cohorts, poor outcome groups exhibited increased ER, MYC signaling, and oxidative phosphorylation, supporting that these pathways are important for DCIS recurrence and progression. Conclusion. Comprehensive genomic profiling in two independent DCIS cohorts with longitudinal outcomes shows distinct DCIS stromal expression patterns and immune cell composition. RNA expression profiles reveal underlying tumor biology that is associated with later iBEs in both cohorts. These studies provide new insight into DCIS biology and will guide the design of diagnostic strategies to prevent invasive progression. Citation Format: Siri H Strand, Belén Rivero-Gutiérrez, Kathleen E Houlahan, Jose A Seoane, Lorraine M King, Tyler Risom, Lunden Simpson, Sujay Vennam, Aziz Khan, Timothy Hardman, Bryan E Harmon, Fergus J Couch, Kristalyn Gallagher, Mark Kilgore, Shi Wei, Angela DeMichele, Tari King, Priscilla F McAuliffe, Julie Nangia, Joanna Lee, Jennifer Tseng, Anna Maria Storniolo, Alastair Thompson, Gaorav Gupta, Robyn Burns, Deborah J Veis, Katherine DeSchryver, Chunfang Zhu, Magdalena Matusiak, Jason Wang, Shirley X Zhu, Jen Tappenden, Daisy Yi Ding, Dadong Zhang, Jingqin Luo, Shu Jiang, Sushama Varma, Cody Straub, Sucheta Srivastava, Christina Curtis, Rob Tibshirani, Robert Michael Angelo, Allison Hall, Kouros Owzar, Kornelia Polyak, Carlo Maley, Jeffrey R Marks, Graham A Colditz, E Shelley Hwang, Robert B West. The Breast PreCancer Atlas DCIS genomic signatures define biology and correlate with clinical outcomes: An analysis of TBCRC 038 and RAHBT cohorts [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-07.

Ductal carcinoma in situ; Tumor microenvironment; Whole genome sequencing Carcinoma ductal in situ; Microambiente tumoral; Secuenciación del genoma completo Carcinoma ductal in situ; Microambient tumoral; Seqüenciació del genoma complet Ductal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We perform multiscale, integrated molecular profiling of DCIS with clinical outcomes by analyzing 774 DCIS samples from 542 patients with 7.3 years median follow-up from the Translational Breast Cancer Research Consortium 038 study and the Resource of Archival Breast Tissue cohorts. We identify 812 genes associated with ipsilateral recurrence within 5 years from treatment and develop a classifier that predicts DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions are identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome. This publication is part of the HTAN (Human Tumor Atlas Network) Consortium paper package. A list of HTAN members is available at humantumoratlas.org/htan-authors/. R01 CA185138-01 (E.S.H.); U2C CA-17-035 Pre-Cancer Atlas (PCA) Research Centers (E.S.H., R.B.W., C.M., K.P., G.A.C., K.O.); UO1 CA214183 (J.R.M.); DOD BC132057 (E.S.H., C.M.); BCRF 19-074 (E.S.H.); BCRF 19-028 (G.A.C.); PRECISION CRUK Grand Challenge (E.S.H.); R01CA193694 (R.B.W., G.A.C.), BCRF PPI-18-006 (R.B.W.). AEI RYC2019- 026576-I, "LaCaixa" Foundation LCF/PR/PR17/51120011 (J.A.S.). S.H.S. was supported by the Lundbeck Foundation (R288-2018-35) and the Danish Cancer Society (R229-A13616). K.E.H. was supported by a CIHR Banting Postdoctoral Fellowship. TBCRC 038 was conducted by the TBCRC, which receives major funding support from The Breast Cancer Research Foundation and Susan G. Komen. Some results in this paper are based upon data generated by the TCGA Research Network.

Metabolic reprogramming of tumor cells and the increase of glucose uptake is one of the hallmarks of cancer. In order to identify metabolic pathways activated in leiomyosarcoma (LMS), we analyzed transcriptomic profiles of distinct subtypes of LMS in several datasets. Primary, recurrent and metastatic tumors in the subtype 2 of LMS showed consistent enrichment of genes involved in hexosamine biosynthesis pathway (HBP). We demonstrated that glutamine-fructose-6-phosphate transaminase 2 (GFPT2), the rate-limiting enzyme in HBP, is expressed on protein level in a subset of LMS and the expression of this enzyme is frequently retained in patient-matched primary and metastatic tumors. In a new independent cohort of 327 patients, we showed that GFPT2 is associated with poor outcome of uterine LMS but not extra-uterine LMS. Based on the analysis of a small group of patients studied by 18F-FDG-PET imaging, we propose that strong expression of GFPT2 in primary LMS may be associated with high metabolic activity. Our data suggest that HBP is a potential new therapeutic target in one of the subtypes of LMS.

Nasopharyngeal cancer (NPC) is an Epstein-Barr virus (EBV)–positive epithelial malignancy with an extensive inflammatory infiltrate. Traditional RNA-sequencing techniques uncovered only microenvironment signatures, while the gene expression of the tumor epithelial compartment has remained a mystery. Here, we use Smart-3SEQ to prepare transcriptome-wide gene expression profiles from microdissected NPC tumors, dysplasia, and normal controls. We describe changes in biological pathways across the normal to tumor spectrum and show that fibroblast growth factor (FGF) ligands are overexpressed in NPC tumors, while negative regulators of FGF signaling, including SPRY1, SPRY2, and LGALS3, are down-regulated early in carcinogenesis. Within the NF-κB signaling pathway, the critical noncanonical transcription factors, RELB and NFKB2, are enriched in the majority of NPC tumors. We confirm the responsiveness of EBV-positive NPC cell lines to targeted inhibition of these pathways, reflecting the heterogeneity in NPC patient tumors. Our data comprehensively describe the gene expression landscape of NPC and unravel the mysteries of receptor tyrosine kinase and NF-κB pathways in NPC.

Background The acquisition of oncogenic drivers is a critical feature of cancer progression. For some carcinomas, it is clear that certain genetic drivers occur early in neoplasia and others late. Why these drivers are selected and how these changes alter the neoplasia’s fitness is less understood. Methods Here we use spatially oriented genomic approaches to identify transcriptomic and genetic changes at the single-duct level within precursor neoplasia associated with invasive breast cancer. We study HER2 amplification in ductal carcinoma in situ (DCIS) as an event that can be both quantified and spatially located via fluorescence in situ hybridization (FISH) and immunohistochemistry on fixed paraffin-embedded tissue. Results By combining the HER2-FISH with the laser capture microdissection (LCM) Smart-3SEQ method, we found that HER2 amplification in DCIS alters the transcriptomic profiles and increases diversity of copy number variations (CNVs). Particularly, interferon signaling pathway is activated by HER2 amplification in DCIS, which may provide a prolonged interferon signaling activation in HER2-positive breast cancer. Multiple subclones of HER2-amplified DCIS with distinct CNV profiles are observed, suggesting that multiple events occurred for the acquisition of HER2 amplification. Notably, DCIS acquires key transcriptomic changes and CNV events prior to HER2 amplification, suggesting that pre-amplified DCIS may create a cellular state primed to gain HER2 amplification for growth advantage. Conclusion By using genomic methods that are spatially oriented, this study identifies several features that appear to generate insights into neoplastic progression in precancer lesions at a single-duct level.

Odontogenic tumors show considerable morphologic heterogeneity and at times the diagnosis can be challenging. Ameloblastoma, the most common odontogenic tumor, can have morphological similarity to some salivary gland tumors and therefore we sought to identify biomarkers that might aid in the diagnosis by performing transcriptome wide gene expression profiling of 80 odontogenic and salivary gland neoplasms. These data identified the FOXP1+/SOX10− expression profile as characteristic of many odontogenic tumors including ameloblastoma but largely absent in salivary gland tumors. We then assessed 173 salivary gland tumors and 108 odontogenic tumors by immunohistochemistry for FOXP1 and SOX10 expression and found that 34/35 (97%) cases of ameloblastomas were diffusely positive for FOXP1 but completely negative for SOX10. None of the basaloid salivary neoplasms (basal cell adenoma, adenoid cystic carcinoma, polymorphous adenocarcinoma, and myoepitheloma) demonstrated FOXP1+/SOX10− expression pattern. Taken together, the results of this study suggest that the FOXP1+/SOX10− immunophenotype is common in odontogenic tumors including ameloblastoma and might be useful distinguishing these from similar appearing basaloid salivary gland tumors.

PURPOSE The preoperative distinction between uterine leiomyoma (LM) and leiomyosarcoma (LMS) is difficult, which may result in dissemination of an unexpected malignancy during surgery for a presumed benign lesion. An assay based on circulating tumor DNA (ctDNA) could help in the preoperative distinction between LM and LMS. This study addresses the feasibility of applying the two most frequently used approaches for detection of ctDNA: profiling of copy number alterations (CNAs) and point mutations in the plasma of patients with LM. PATIENTS AND METHODS By shallow whole-genome sequencing, we prospectively examined whether LM-derived ctDNA could be detected in plasma specimens of 12 patients. Plasma levels of lactate dehydrogenase, a marker suggested for the distinction between LM and LMS by prior studies, were also determined. We also profiled 36 LM tumor specimens by exome sequencing to develop a panel for targeted detection of point mutations in ctDNA of patients with LM. RESULTS We identified tumor-derived CNAs in the plasma DNA of 50% (six of 12) of patients with LM. The lactate dehydrogenase levels did not allow for an accurate distinction between patients with LM and patients with LMS. We identified only two recurrently mutated genes in LM tumors ( MED12 and ACLY). CONCLUSION Our results show that LMs do shed DNA into the circulation, which provides an opportunity for the development of ctDNA-based testing to distinguish LM from LMS. Although we could not design an LM-specific panel for ctDNA profiling, we propose that the detection of CNAs or point mutations in selected tumor suppressor genes in ctDNA may favor a diagnosis of LMS, since these genes are not affected in LM.

Multiplexed ion beam imaging by time-of-flight (MIBI-TOF) is a form of mass spectrometry imaging that uses metal labeled antibodies and secondary ion mass spectrometry to image dozens of proteins simultaneously in the same tissue section. Working with the National Cancer Institute's (NCI) Cancer Immune Monitoring and Analysis Centers (CIMAC), we undertook a validation study, assessing concordance across a dozen serial sections of a tissue microarray of 21 samples that were independently processed and imaged by MIBI-TOF or single-plex immunohistochemistry (IHC) over 12 days. Pixel-level features were highly concordant across all 16 targets assessed in both staining intensity (R

Cellular composition and structural organization of cells in the tissue determine effective antitumor response and can predict patient outcome and therapy response. Here we present Seg-SOM, a method for dimensionality reduction of cell morphology in H&E-stained tissue images. Seg-SOM resolves cellular tissue heterogeneity and reveals complex tissue architecture. We leverage a self-organizing map (SOM) artificial neural network to group cells based on morphological features like shape and size. Seg-SOM allows for cell segmentation, systematic classification, and in silico cell labeling. We apply the Seg-SOM to a dataset of breast cancer progression images and find that clustering of SOM classes reveals groups of cells corresponding to fibroblasts, epithelial cells, and lymphocytes. We show that labeling the Lymphocyte SOM class on the breast tissue images accurately estimates lymphocytic infiltration. We further demonstrate how to use Seq-SOM in combination with non-negative matrix factorization to statistically describe the interaction of cell subtypes and use the interaction information as highly interpretable features for a histological classifier. Our work provides a framework for use of SOM in human pathology to resolve cellular composition of complex human tissues. We provide a python implementation and an easy-to-use docker deployment, enabling researchers to effortlessly featurize digitalized H&E-stained tissue.

Cancer cells rewire metabolic pathways and energy production to support the enhanced proliferation, invasion and resistance to treatment. The three main glucose metabolism pathways that support growth of cancer cells are: a) the glycolysis pathway for energy production; b) the pentose phosphate pathway for biomass production; and c) the hexosamine biosynthesis pathway (HBP) for protein glycosylation. It is known that the activation of HBP leads to altered glycosylation of oncogenes, transcription factors and kinases in many types of cancer. These aberrations may lead to increased proliferation and survival of tumor cells, and may be associated with resistance to therapy. A better understanding of the role of HBP in malignancies has the potential for clinical implications. Several studies demonstrated that pharmacological inhibition of GFPT2 (glutamine-fructose-6-phosphate transaminase 2, the first and rate-limiting enzyme in HBP) and the enzymes that act downstream of HBP may exhibit anti-tumorigenic effect both in vitro and in vivo, and may modulate sensitivity to chemo-, radio- and immunotherapy. Most of these studies focused on carcinomas and the role of HPB in sarcoma has not been studied. We recently reported a remarkable enrichment of genes involved in HBP in a subset of leiomyosarcoma (LMS) and demonstrated that expression of GFPT2 in LMS is associated with poor clinical outcome. We identified the c-Myc oncoprotein as a potential target of HPB that may be stabilized by aberrant glycosylation in LMS. Here we show the results of a large-scale screening of 260 primary specimens of 33 types of soft tissue lesions. In addition to expression in a subset of LMS, we observed near universal expression of GFPT2 in 34 of 35 desmoid type fibromatosis (DTF), independent of the mutation type of the CTNNB1 gene. Gene Set Enrichment Analysis of a previously published 3SEQ transcriptomic dataset composed of DTF and 9 other types of fibrotic lesions identified significant enrichment of other genes implicated in HBP and multiple glycosylation-associated pathways in DTF compared to the other types of fibrotic lesions. Our analysis identified ATF6 (activating transcription factor 6) as a possible target regulated by aberrant glycosylation as a consequence of HBP activation in DTF. ATF6 is a glycoprotein that has been demonstrated to underlie the resistance to chemotherapy in osteosarcoma, to have a pro-oncogenic role in primary liver cancers and has been proposed as a therapeutic target in cystic fibrosis. Others have shown that targeting HBP can provide therapeutic benefit in a number of preclinical models of carcinoma. Our studies offer new insights into the mechanisms of DTF tumorigenesis and, when confirmed by in vitro studies, will provide a rationale to explore the potential of therapeutic targeting of HBP in DTF. Citation Format: Joanna Przybyl, Angela Tolwani, Sushama Varma, Matt van de Rijn. Targeting hexosamine biosynthesis pathway for the treatment of desmoid tumors [abstract]. In: Proceedings of the AACR Special Conference: Sarcomas; 2022 May 9-12; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2022;28(18_Suppl):Abstract nr B015.

Cellular composition and structural organization of cells in the tissue determine effective antitumor response and can predict patient outcome and therapy response. Here we present Seg-SOM, a method for dimensionality reduction of cell morphology in H&E-stained tissue images. Seg-SOM resolves cellular tissue heterogeneity and reveals complex tissue architecture. We leverage a self-organizing map (SOM) artificial neural network to group cells based on morphological features like shape and size. Seg-SOM allows for cell segmentation, systematic classification, and in silico cell labeling. We apply the Seg-SOM to a dataset of breast cancer progression images and find that clustering of SOM classes reveals groups of cells corresponding to fibroblasts, epithelial cells, and lymphocytes. We show that labeling the Lymphocyte SOM class on the breast tissue images accurately estimates lymphocytic infiltration. We further demonstrate how to use Seq-SOM in combination with non-negative matrix factorization to statistically describe the interaction of cell subtypes and use the interaction information as highly interpretable features for a histological classifier. Our work provides a framework for use of SOM in human pathology to resolve cellular composition of complex human tissues. We provide a python implementation and an easy-to-use docker deployment, enabling researchers to effortlessly featurize digitalized H&E-stained tissue.

SUMMARYDuctal carcinoma in situ (DCIS) is the most common precursor of invasive breast cancer (IBC), with variable propensity for progression. We have performed the first multiscale, integrated profiling of DCIS with clinical outcomes by analyzing 677 DCIS samples from 481 patients with 7.1 years median follow-up from the Translational Breast Cancer Research Consortium (TBCRC) 038 study and the Resource of Archival Breast Tissue (RAHBT) cohorts. We identified 812 genes associated with ipsilateral recurrence within 5 years from treatment and developed a classifier that was predictive of DCIS or IBC recurrence in both cohorts. Pathways associated with recurrence include proliferation, immune response, and metabolism. Distinct stromal expression patterns and immune cell compositions were identified. Our multiscale approach employed in situ methods to generate a spatially resolved atlas of breast precancers, where complementary modalities can be directly compared and correlated with conventional pathology findings, disease states, and clinical outcome.HIGHLIGHTS⍰ Development of a new classifier for DCIS recurrence or progression⍰ Outcome associated pathways identified across multiple data types and compartments⍰ Four stroma-specific signatures identified⍰ CNAs characterize DCIS subgroups associated with high risk invasive cancers