Stephen Martis’s research while affiliated with Memorial Sloan Kettering Cancer Center and other places
What is this page?
This page lists works of an author who doesn't have a ResearchGate profile or hasn't added the works to their profile yet. It is automatically generated from public (personal) data to further our legitimate goal of comprehensive and accurate scientific recordkeeping. If you are this author and want this page removed, please let us know.
Regulatory T (Treg) cells are a specialized CD4⁺ T cell lineage with essential anti-inflammatory functions. Analysis of Treg cell adaptations to non-lymphoid tissues that enable their specialized immunosuppressive and tissue-supportive functions raises questions about the underlying mechanisms of these adaptations and whether they represent stable differentiation or reversible activation states. Here, we characterize distinct colonic effector Treg cell transcriptional programs. Attenuated T cell receptor (TCR) signaling and acquisition of substantial TCR-independent functionality seems to facilitate the terminal differentiation of a population of colonic effector Treg cells that are distinguished by stable expression of the immunomodulatory cytokine IL-10. Functional studies show that this subset of effector Treg cells, but not their expression of IL-10, is indispensable for colonic health. These findings identify core features of the terminal differentiation of effector Treg cells in non-lymphoid tissues and their function.
Tertiary lymphoid structures (TLSs) are de novo ectopic lymphoid aggregates that regulate immunity in chronically inflamed tissues, including tumours. Although TLSs form due to inflammation-triggered activation of the lymphotoxin (LT)–LTβ receptor (LTβR) pathway¹, the inflammatory signals and cells that induce TLSs remain incompletely identified. Here we show that interleukin-33 (IL-33), the alarmin released by inflamed tissues², induces TLSs. In mice, Il33 deficiency severely attenuates inflammation- and LTβR-activation-induced TLSs in models of colitis and pancreatic ductal adenocarcinoma (PDAC). In PDAC, the alarmin domain of IL-33 activates group 2 innate lymphoid cells (ILC2s) expressing LT that engage putative LTβR⁺ myeloid organizer cells to initiate tertiary lymphoneogenesis. Notably, lymphoneogenic ILC2s migrate to PDACs from the gut, can be mobilized to PDACs in different tissues and are modulated by gut microbiota. Furthermore, we detect putative lymphoneogenic ILC2s and IL-33-expressing cells within TLSs in human PDAC that correlate with improved prognosis. To harness this lymphoneogenic pathway for immunotherapy, we engineer a recombinant human IL-33 protein that expands intratumoural lymphoneogenic ILC2s and TLSs and demonstrates enhanced anti-tumour activity in PDAC mice. In summary, we identify the molecules and cells of a druggable pathway that induces inflammation-triggered TLSs. More broadly, we reveal a lymphoneogenic function for alarmins and ILC2s.
Tumor specific neoantigens, encoded by somatic mutations, are recognized by T cells, inducing anti-tumor immune responses. This renders neoantigens viable targets for personalized cancer vaccines. However, the identification of immunogenic neoantigens remains suboptimal. Understanding how immune selective pressure-mediated tumor evolution and neoantigen editing contribute to emergence of immunogenic neoantigens may improve prediction accuracy. In this study, we aimed to model tumor evolution and heterogeneity under immune pressure using three preclinical models of lung cancer with common driver mutations, Kras G12D/+ and p53 -/-, namely KPA, KPC, and HKP1, subcutaneously implanted in immunocompetent C57BL/6 (B6) and immune-deficient Rag1-/- mice. Our data suggest that despite shared driver mutations identified by whole exome and RNA-seq, tumor growth in vivo varied between tumor models. KPA tumors were immunogenic, as they were controlled in B6 mice but rapidly progressed in Rag1-/- mice, suggesting immunoediting of KPA-specific neoantigens. In contrast, HKP1 was non-immunogenic, with tumors progressing regardless of immune competency. KPC showed moderate tumor control in B6 mice, which was lost in Rag1-/- mice. We then estimated the cancer cell fraction on every mutation based on phylogenetic reconstruction. Immunogenic KPA tumors had significantly lower mutation burden in B6 than in Rag1-/- mice and the fraction of cell line mutations edited in vivo was significantly higher, suggesting active immunoediting in the former. Non-immunogenic HKP1 tumors did not show significant differences in mutation burden nor fraction of mutations edited between B6 and Rag1-/- mice. The immunogenicity was reflected in the immune infiltrate levels within tumors, with KPA being highly infiltrated by activated CD4 and CD8 T cells compared to KPC. HKP1 tumors showed increased infiltration of suppressive regulatory T cells. T cell receptor (TCR) sequencing on lung tumors showed that clonal expansion is strongly associated with immunogenicity. KPA tumors showed significantly higher TCR clustering with less diversity compared to KPC and more than HKP1. Following a simple approach to study the immunogenicity of shared neoantigens to elicit cross-protective anti-tumor responses, mice were immunized with whole irradiated (IR) tumor cell lines and implanted with live tumor cells (matched and unmatched). While immunization with IR-KPA protected against corresponding tumor implant and moderately against KPC, it did not protect against HKP1, indicating lack of immunogenicity of mutations shared between KPA and HKP1. Further studies testing the anti-tumor responses and characteristics of neoantigens shared between these three related tumor cell lines will inform the conditions under which tumors may escape or regress and help improve neoantigen identifying algorithms.
Citation Format: Mariam Mathew George, Jayon Lihm, Hyejin Choi, Yuval Elhanati, Stephen Martis, Marta Luksza, Benjamin Greenbaum, Jedd D. Wolchok, Taha Merghoub. Modeling tumor immunoediting under immune selective pressure to inform neoantigen landscape dynamics for effective cancer vaccines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4093.
Purpose: Pancreatic cancer is a lethal malignancy characterized by complex intratumoral metabolic reprogramming and intercellular nutrient sharing between cells in the tumor microenvironment (TME) that promote pancreatic cancer progression. However, this crosstalk, as well as regional variation in perfusion and oxygenation, can lead to metabolic heterogeneity that has not been appreciated by metabolomics of whole tumors. Here we quantify amino acids and tricarboxylic acid cycle (TCA) intermediates using a novel methodology that allows us to portray global tumor metabolite heterogeneity in a tumor.
Methods: Human PaTu-8902 or murine HY19636 (from female KPC mice LSL-KrasG12D; p53 L/+, Ptf1a-Cre+) pancreatic cancer cell lines were orthotopically injected into pancreata of NCr nude mice (n=3) or C57BL/6 mice (n=2). Mice were euthanized after 3-5 weeks and tumors were harvested. Tumor slices were further sectioned into 1mm x 1mm x 1mm cubes using a custom-made multisectional slicing device and each cube location was recorded. Each cube was extracted using methanol, water, and chloroform with labelled amino acid standards, derivitized, and resolved using gas chromatography-mass spectrometry (DB-35MS column with Agilent 7890B gas chromatograph coupled to a single quadrupole 5977B mass spectrometer). 22 metabolites (15 amino acids, 5 TCA intermediates, lactate, and pyruvate) were identified by unique fragments and retention time compared to known standards. Peaks were picked using OpenChrom and analyzed using MATLAB. Data was analyzed using Graphpad Prism. Principal Component Analysis (PCA) was visualized using Python on a Jupyter notebook.
Results: Both orthotopic human and murine pancreatic tumors demonstrated striking levels of intratumoral metabolite heterogeneity. Glycine, glutamine, and proline were the amino acids with the highest coefficient of variance, while leucine, isoleucine, and serine had the lowest coefficient of variance. α-ketoglutarate and succinate were the TCA intermediates with highest coefficient of variance. Lactate had the lowest coefficient of variance among all examined metabolites. Spatial mapping of each metabolite demonstrated distinct regions with varying abundance levels of metabolites. PCA demonstrated 75% of variance was carried by PC1 and 10% carried by PC2.
Conclusions: This study reveals insights into the degree of intratumoral heterogeneity present in pancreatic tumors that illustrate the difficulty of in vivo metabolomics analysis and suggest that high-resolution (single cell) metabolomics techniques will be critical to study metabolism in the complex TME.
Citation Format: Peter Yu, Robert Banh, Albert Sohn, Stephen Martis, Douglas Biancur, Keisuke Yamamoto, Elaine Lin, Alec Kimmelman. Topographical investigation of metabolites in excised squares (TIMES2): Comprehensive cross-sectional metabolite quantification of pancreatic cancer in vivo [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4440.
Background: Pancreatic cancer is a lethal malignancy characterized by complex intratumoral metabolic reprogramming and intercellular nutrient sharing between cells in the tumor microenvironment (TME) that promote pancreatic cancer progression. However, this crosstalk, as well as regional variation in perfusion and oxygenation, can lead to metabolic heterogeneity that has not been appreciated by metabolomics of whole tumors. Here we quantify amino acids and tricarboxylic acid cycle (TCA) intermediates using a novel methodology that allows us to portray global tumor metabolite heterogeneity in a tumor. Methods: Human PaTu-8902 or murine HY19636 (from female KPC mice p48-Cre+, KRASLSL-G12D/+, Trp53lox/+) pancreatic cancer cell lines were orthotopically injected into pancreata of NCr nude mice (n=3) or C57BL/6 mice (n=2). Mice were euthanized after 3-5 weeks and tumors were harvested. Tumor slices were further sectioned into 1mm x 1mm x 1mm cubes using a custom-made multisectional slicing device and each cube location was recorded. Each cube was extracted using methanol, water, and chloroform with labelled amino acid standards, derivitized, and resolved using gas chromatography-mass spectrometry (DB-35MS column with Agilent 7890B gas chromatograph coupled to a single quadrupole 5977B mass spectrometer). 22 metabolites (15 amino acids, 5 TCA intermediates, lactate, and pyruvate) were identified by unique fragments and retention time compared to known standards. Peaks were picked using OpenChrom and analyzed using MATLAB. Data was analyzed using Graphpad Prism. Principal Component Analysis (PCA) was visualized using Python on a Jupyter notebook. Results: Both orthotopic human and murine pancreatic tumors demonstrated striking levels of intratumoral metabolite heterogeneity. Glycine, glutamine, and proline were the amino acids with the highest coefficient of variance, while leucine, isoleucine, and serine had the lowest coefficient of variance. α-ketoglutarate and succinate were the TCA intermediates with highest coefficient of variance. Lactate had the lowest coefficient of variance among all examined metabolites. Spatial mapping of each metabolite demonstrated distinct regions with varying abundance levels of metabolites. PCA demonstrated 75% of variance was carried by PC1 and 10% carried by PC2. Conclusions: This study reveals insights into the degree of intratumoral heterogeneity present in pancreatic tumors that illustrate the difficulty of in vivo metabolomics analysis and suggest that high-resolution (single cell) metabolomics techniques will be critical to study metabolism in the complex TME.
Citation Format: Peter Yu, Robert Banh, Stephen Martis, Douglas Biancur, Albert Sohn, Elaine Lin, Keisuke Yamamoto, Benjamin Greenbaum, Alec Kimmelman. Topographical investigation of metabolites in excised squares (TIMES2): Mapping in vivo of metabolic heterogeneity in pancreatic tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Pancreatic Cancer; 2023 Sep 27-30; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(2 Suppl):Abstract nr C054.
Background
In contrast to PD-1⁺CD8⁺ T cells, PD-1⁺CD4⁺ T cells and their impact in tumor progression and immunotherapy response remain relatively unexplored. We previously reported that PD-1hiFoxp3⁻CD4⁺ T cells (4PD1hi) from melanoma-bearing mice and patients with melanoma or non-small cell lung cancer (NSCLC) suppress T-cell function and correlate with unfavorable outcomes upon immune checkpoint blockade (ICB) therapy.¹ CD4⁺PD-1⁺ T cells were also found to correlate with poor prognosis in other NSCLC patient cohorts.2–4 We showed that 4PD1hiup-regulate T-follicular-helper-cell(Tfh)-related genes.¹ 4PD1hi cells suppressing immunotherapy responses were recently described in mouse sarcoma models; however, in this setting, 4PD1hi did not over-express Tfh genes.⁵ Here, we sought to deconvolve the lineage commitment of 4PD1hi tumor-infiltrating lymphocytes (TILs) in relationship with their immune function and impact on ICB outcome.
Methods
Single-cell RNA-sequencing (scRNAseq) was performed in 4PD1hi, PD-1⁻Foxp3⁻CD4⁺ (4Dneg), and Foxp3⁺CD4⁺ T cells (Tregs) FACS-sorted from ICB-treated B16F10-melanoma bearing Foxp3-GFP mice. scRNAseq datasets of TILs from ICB-treated cancer patients6–9 were used to extract 4PD1hi and analyze their profiles. Tfh-deficient SAP knock-out (KO) and CD4KO:CXCR5KO mixed bone marrow (BM) transplanted RAGKO and control mice were implanted with B16F10, treated with ICB, and 4PD1hi, 4Dneg, and Tregs were quantified by flow cytometry and FACS-sorted for functional analyses.
Results
Using prior-knowledge-based signatures and mutual-information-based cell-type classification,¹⁰ we found that spleen-derived 4PD1hi cells from tumor-bearing mice polarize toward Tfh, Tregs toward a canonical Treg phenotype, and 4Dneg toward Th1. Conversely, tumor-derived 4PD1hi were not significantly skewed toward these phenotypes but gained in Th1 polarization after an effective anti-CTLA-4 treatment. In human primary melanoma,⁷ NSCLC,⁶ and squamous/basal cell carcinoma,⁸ 4PD1hi cells over-expressed Tfh-related genes. This was less clear in 4PD1hi from mixed NSCLC samples, encompassing primary tumors and different metastatic sites.⁹ However, 4PD1hi from ICB-non-responder patients in this study⁹ displayed the greatest Tfh-signature scores. Consistently, 4PD1hi TILs from ICB-non-responders in the other NSCLC and melanoma datasets up-regulated Tfh-related genes. To test 4PD1hi TIL Tfh polarization in ICB response, we used SAPKO and CD4KO:CXCR5KO BM chimera mice. Both Tfh-deficient models showed better tumor responses to a suboptimal anti-CTLA-4 treatment¹; however, 4PD1hi TILs did not substantially decrease. In this setting, 4PD1hi TILs lost suppressive function, down-regulated Pdcd1 and Il10, and up-regulated Ifng, suggesting a Th1 phenotypic switch.
Conclusions
These results indicate that 4PD1hi TILs are heterogeneous and their Tfh/Th1 polarization influences immunotherapy responses possibly in a tumor-tissue dependent way. In melanoma, 4PD1hi TIL Tfh polarization drives immunosuppression and ICB resistance.
Acknowledgements
This study was supported in part by the Parker Institute for Cancer Immunotherapy. S. M. and A.O. contributed equally to this work.
References
• Zappasodi R, Budhu S, Hellmann MD, Postow MA, Senbabaoglu Y, Manne S, et al. Non-conventional Inhibitory CD4(+)Foxp3(-)PD-1(hi) T Cells as a Biomarker of Immune Checkpoint Blockade Activity. Cancer Cell. 2018;
33
(6):1017–32 e7.
• Zheng H, Liu X, Zhang J, Rice SJ, Wagman M, Kong Y, et al. Expression of PD-1 on CD4 + T cells in peripheral blood associates with poor clinical outcome in non-small cell lung cancer. Oncotarget. 2016;
7
(35).
• Arrieta O, Montes-Servín E, Hernandez-Martinez J-M, Cardona AF, Casas-Ruiz E, Crispín JC, et al. Expression of PD-1/PD-L1 and PD-L2 in peripheral T-cells from non-small cell lung cancer patients. Oncotarget. 2017;
8
(60).
• Duchemann B, Naigeon M, Auclin E, Ferrara R, Cassard L, Jouniaux JM, et al. CD8(+)PD-1(+) to CD4(+)PD-1(+) ratio (PERLS) is associated with prognosis of patients with advanced NSCLC treated with PD-(L)1 blockers. J Immunother Cancer. 2022;
10
(2).
• Hussein S, Kelly M, Yuang S, Samuel A, Ton S, Yik Andy Y, et al. 578 CD8-targeted IL-2 drives potent anti-tumor efficacy and promotes action of tumor specific vaccines. Journal for ImmunoTherapy of Cancer. 2021;
9
(Suppl 2):A607.
• Caushi JX, Zhang J, Ji Z, Vaghasia A, Zhang B, Hsiue EH, et al. Transcriptional programs of neoantigen-specific TIL in anti-PD-1-treated lung cancers. Nature. 2021;
596
(7870):126–32.
• Schad SE, Chow A, Mangarin L, Pan H, Zhang J, Ceglia N, et al. Tumor-induced double positive T cells display distinct lineage commitment mechanisms and functions. J Exp Med. 2022;
219
(6).
• Yost KE, Satpathy AT, Wells DK, Qi Y, Wang C, Kageyama R, et al. Clonal replacement of tumor-specific T cells following PD-1 blockade. Nat Med. 2019;
25
(8):1251–9.
• Liu B, Hu X, Feng K, Gao R, Xue Z, Zhang S, et al. Temporal single-cell tracing reveals clonal revival and expansion of precursor exhausted T cells during anti-PD-1 therapy in lung cancer. Nature Cancer. 2022;
3
(1):108–21.
• Ceglia N, Sethna Z, Freeman SS, Uhlitz F, Bojilova V, Rusk N, et al. GeneVector: Identification of transcriptional programs using dense vector representations defined by mutual information. bioRxiv. 2023:2022.04.22.487554.
Retrotransposons are genetic elements that have the ability to copy and paste themselves in the genome via the proteins they encode. Since the rapid growth of a retrotransposon can be highly deleterious at the organismal level, many of these genetic parasites are suppressed or have been inactivated over evolutionary time. However, the human genome still hosts the active retrotransposon LINE-1, whose aberrant expression is associated with various diseases, especially epithelial cancers. Despite these associations, a quantitative understanding of the dynamics and diversity of LINE-1 insertions in somatic tissue is lacking. In order to address this gap, we present a population dynamic model of LINE-1 retrotransposition in individual cells. Using the model, we show that at demographic equilibrium, the LINE-1 copy number distribution is broader than would be expected from classical population genetic models. We demonstrate how this broadening distorts the frequency spectrum of insertions. We compare the model's predictions to data from whole genome sequencing of individual tumor cells.
Citation Format: Stephen Martis, Alexander Solovyov, Jayon Lihm, Hao Li, Benjamin Greenbaum. The dynamics of LINE-1 retrotransposition in cellular populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 860.
Citations (1)
... Одной из важных неподвижных фаз, селективность которой отличается от селективности стандартных неподвижных фаз, является 35%-фенил-метилполиси-локсан. Эти неподвижные фазы (например, DB-35, DB-35MS, OV-35) широко используются в аналитической практике [12][13][14], в том числе в новейших работах [15][16]. Работ по прогнозированию удерживания для них крайне мало, в частности, есть работы по прогнозированию удерживания замещенных полихлорированных бифенилов [17][18]. ...