Search

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 Table S1. In vivo limiting dilution analyses of P-LSCC and K/P-LSCC. Supplementary Table S3. Likely zygosity and functional effects of KEAP1 mutations in NSCLC patients in Fig. 7A. Supplementary Table S4. Clinical characteristics of a validation cohort of stage I-III NSCLC patients treated with curative intent RT and analyzed for KEAP1/NRF2 mutation status using targeted next generation sequencing. Antibodies used in this study.

Supplementary Figure S1. Loss of Keap1 or Trp53 promotes airway basal stem cell self-renewal. Supplementary Figure S2. Lineage tracing method for airway basal stem cells. Supplementary Figure S3. Characterization of LSCCs derived from Keap1-/-;Trp53-/- or Trp53-/- tracheal cells. Supplementary Figure S4. Airway basal stem cells are the cell of origin for Trp53-/- and Keap1-/-;Trp53-/- LSCCs. Supplementary Figure S5. Gene expression analysis of P-LSCC and K/P-LSCC tumors. Supplementary Figure S6. Loss of Keap1 in LSCCs leads to protection from oxidative stress. Supplementary Figure S7. Loss of Keap1 in LSCCs leads to protection from ionizing irradiation. Supplementary Figure S8. Inhibition of xCT sensitizes radioresistant K/P-LSCCs. Supplementary Figure S9. TP53 mutation status is not associated with local failure after radiotherapy in human NSCLC patients.

Supplemental methods

Supplemental Tables S1-S12

Figures S1-S10

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.

PDF file, 393K, The results of the survival analysis of the lung tumors in lung cancer datasets including caArray-beer-00153 (Supp Fig4A), GSE4573 (Supp Fig4B), GSE10445 (Supp Fig4C), GSE10245 (Supp Fig4D) and GSE11969 (Supp Fig4E).

Supplemental Figure 1. Patient inclusion and exclusion criteria. TNBC: triple negative breast cancer; ALC: absolute lymphocyte count; nSES: neighborhood socioeconomic status. Supplemental Figure 2a and 2b. Association between minimum lymphocyte count (as percentage of total white blood cell count and absolute value) and stromal tumor infiltrating lymphocytes (sTILs), N=77. Figure 2a. sTILs were correlated with minimum % lymphocyte (p=0.02). Figure 2b. sTILs did not have a significant correlation with minimum absolute (abs) lymphocytes (p=0.36) Supplemental Figure 3. Comparison between Absolute Lymphocyte Count (ALC) and percent peripheral lymphocytes Supplemental Figure 4. Distribution of Absolute Lymphocyte Count (ALC) measures at baseline, defined as ALC value measured within the first three months of breast cancer diagnosis. Supplemental Figure 5. Distribution of minimum Absolute Lymphocyte Count (ALC) values at any time point Supplemental Figure 6. Distribution of overall minimum Absolute Lymphocyte Count (ALC) over time Supplemental Table 1. Multivariable analysis of predictors of lymphopenia (absolute lymphocyte count [ALC]

PDF file, 35K.

This supplement file contains the identified SUVmax correlated genes in the lung squamous cell carcinoma patients in the RG cohort.

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: 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.

Purpose: Tumor-infiltrating lymphocytes (TIL) in pretreatment biopsies are associated with improved survival in triple-negative breast cancer (TNBC). We investigated whether higher peripheral lymphocyte counts are associated with lower breast cancer–specific mortality (BCM) and overall mortality (OM) in TNBC.Experimental Design: Data on treatments and diagnostic tests from electronic medical records of two health care systems were linked with demographic, clinical, pathologic, and mortality data from the California Cancer Registry. Multivariable regression models adjusted for age, race/ethnicity, socioeconomic status, cancer stage, grade, neoadjuvant/adjuvant chemotherapy use, radiotherapy use, and germline BRCA1/2 mutations were used to evaluate associations between absolute lymphocyte count (ALC), BCM, and OM. For a subgroup with TIL data available, we explored the relationship between TILs and peripheral lymphocyte counts.Results: A total of 1,463 stage I–III TNBC patients were diagnosed from 2000 to 2014; 1,113 (76%) received neoadjuvant/adjuvant chemotherapy within 1 year of diagnosis. Of 759 patients with available ALC data, 481 (63.4%) were ever lymphopenic (minimum ALC n = 70) showed a significant association between TILs and higher peripheral lymphocyte counts during neoadjuvant chemotherapy.Conclusions: Higher peripheral lymphocyte counts predicted lower mortality from early-stage, potentially curable TNBC, suggesting that immune function may enhance the effectiveness of early TNBC treatment. Clin Cancer Res; 24(12); 2851–8. ©2018 AACR.

PDF file, 753K, The expression profiles of DTF fibroblast core gene signature in three prostate cancer datasets, including GSE1431 (Supp Fig3A), GSE3933 (Supp Fig3B), and GSE25136 (Supp Fig3C).

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

PDF file, 249K, The expression profiles of DTF fibroblast core gene signature in two colon cancer datasets, including GSE 14333 (Supp Fig2A) and GSE17538 (Supp Fig2B). The results of the survival analysis of GSE14333 and GSE17538 were separately shown in Supp Fig2C and Supp Fig2D, Supp Fig2E and Supp Fig2F.

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

PDF file, 911K, The expression profiles of DTF fibroblast core gene signature in five lung cancer datasets, including caArray-beer-00153 (Supp Fig1A), GSE4573 (Supp Fig1B), GSE10245 (Supp Fig1C), GSE10445 (Supp Fig1D) and GSE11969 (Supp Fig1E).

This supplement file contains the identified SUVmax correlated genes in the lung adenocarcinoma patients in the RG cohort.

Purpose: We have previously characterized a tumor stroma expression signature in a subset of breast tumors that correlates with better clinical outcome. The purpose of this study is to determine whether this stromal signature, termed the “DTF fibroblast” (desmoid-type fibromatosis) signature, is specific to breast cancer or is a common stromal response found in different types of cancer.Experimental Designs: The DTF fibroblast signature was applied to gene expression profiles from five ovarian, five lung, two colon, and three prostate cancer expression microarray datasets. In addition, two different tissue microarrays of 204 ovarian tumors and 140 colon tumors were examined for the expression of previously characterized protein markers of DTF fibroblast signature. The DTF fibroblast stromal response was then correlated with clinicopathologic features.Results: The DTF fibroblast signature is robustly present in ovarian, lung, and colon carcinomas. Both expression microarray data and immunohistochemistry show that the subset of ovarian tumors with strong DTF fibroblast signature expression has statistically significant, worse survival outcomes. No reproducible survival differences were found in either the lung or the colon cancers. The prostate cancers failed to show a DTF fibroblast signature. Multivariant analysis showed that DTF fibroblast signature was significantly more prognostic than the proliferation status in ovarian carcinomas.Conclusions: Our results suggest that the DTF fibroblast signature is a common tumor stroma signature in different types of cancer, including ovarian, lung, and colon carcinomas. Our findings provide further insight into the DTF fibroblast stromal responses across different types of carcinomas and their potential as prognostic and therapeutic targets. Clin Cancer Res; 19(18); 5127–35. ©2013 AACR.

This supplement file contains a list of de-identified IDs of the patients included in the RG cohort data available online.

PDF file, 829K, The expression profiles of DTF fibroblast core gene signature in two colon cancer datasets, including GSE 14333 (Supp Fig2A) and GSE17538 (Supp Fig2B). The results of the survival analysis of GSE14333 and GSE17538 were separately shown in Supp Fig2C and Supp Fig2D, Supp Fig2E and Supp Fig2F.

CCR Translation for This Article from Stromal Responses among Common Carcinomas Correlated with Clinicopathologic Features

This supplement file contains the identified differentially expressed genes (DEGs) between lung adenocarcinoma (AD) and squamous cell carcinoma (SCC) patients.

This supplement file provides additional information and analysis descriptions to the main manuscript ordered as in which they appear in the main text. This supplement file also provides general descriptions and overview to all the supplement materials included. This supplement file also includes Figure S1-S7 and Table S1-S3.

Metabolic reprogramming of the tumor microenvironment is recognized as a cancer hallmark. To identify new molecular processes associated with tumor metabolism, we analyzed the transcriptome of bulk and flow-sorted human primary non–small cell lung cancer (NSCLC) together with 18FDG-PET scans, which provide a clinical measure of glucose uptake. Tumors with higher glucose uptake were functionally enriched for molecular processes associated with invasion in adenocarcinoma and cell growth in squamous cell carcinoma (SCC). Next, we identified genes correlated to glucose uptake that were predominately overexpressed in a single cell–type comprising the tumor microenvironment. For SCC, most of these genes were expressed by malignant cells, whereas in adenocarcinoma, they were predominately expressed by stromal cells, particularly cancer-associated fibroblasts (CAF). Among these adenocarcinoma genes correlated to glucose uptake, we focused on glutamine-fructose-6-phosphate transaminase 2 (GFPT2), which codes for the glutamine-fructose-6-phosphate aminotransferase 2 (GFAT2), a rate-limiting enzyme of the hexosamine biosynthesis pathway (HBP), which is responsible for glycosylation. GFPT2 was predictive of glucose uptake independent of GLUT1, the primary glucose transporter, and was prognostically significant at both gene and protein level. We confirmed that normal fibroblasts transformed to CAF-like cells, following TGFβ treatment, upregulated HBP genes, including GFPT2, with less change in genes driving glycolysis, pentose phosphate pathway, and TCA cycle. Our work provides new evidence of histology-specific tumor stromal properties associated with glucose uptake in NSCLC and identifies GFPT2 as a critical regulator of tumor metabolic reprogramming in adenocarcinoma.Significance: These findings implicate the hexosamine biosynthesis pathway as a potential new therapeutic target in lung adenocarcinoma. Cancer Res; 78(13); 3445–57. ©2018 AACR.

PDF file - 73K

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

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).

PDF file - 153K

Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual’s germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes inERBB2,encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an “immune cold” phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.

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.