@article{horwitz_duvelisib_2024,
  title = {Duvelisib plus romidepsin in relapsed/refractory {T} cell lymphomas: a phase 1b/2a trial},
  volume = {30},
  issn = {1546-170X},
  shorttitle = {Duvelisib plus romidepsin in relapsed/refractory {T} cell lymphomas},
  doi = {10.1038/s41591-024-03076-6},
  language = {eng},
  number = {9},
  journal = {Nature Medicine},
  author = {Horwitz, Steven M. and Nirmal, Ajit J. and Rahman, Jahan and Xu, Ran and Drill, Esther and Galasso, Natasha and Ganesan, Nivetha and Davey, Theresa and Hancock, Helen and Perez, Leslie and Maccaro, Catherine and Bahgat, Alexandra and Marzouk, Evan and Cathcart, Elizabeth and Moskowitz, Alison and Noy, Ariela and Kumar, Anita and Jacobsen, Eric and Fisher, David C. and Mehta-Shah, Neha and Kim, Youn H. and Khodadoust, Michael and Kotlov, Nikita and Nikitina, Anastasia and Kudryashova, Olga and Zubareva, Valeria and Zornikova, Ksenia and Shin, Nara and Sorokina, Maria and Degryse, Sandrine and Postovalova, Ekaterina and Bagaev, Aleksander and Hosszu, Kinga and McAvoy, Devin and Boelens, Jaap J. and Wu, Wenchao and Ciantra, Zoe and Appelt, Jackson W. and Trevisani, Christopher and Amaka, Sam and Weinstock, David M. and Vardhana, Santosha A.},
  month = sep,
  year = {2024},
  pmid = {38886623},
  keywords = {Adult, Aged, Aged, 80 and over, Antineoplastic Combined Chemotherapy Protocols, Bortezomib, Depsipeptides, Female, Humans, Isoquinolines, Lymphoma, T-Cell, Male, Maximum Tolerated Dose, Middle Aged, Purines},
  pages = {2517--2527}
}

PI3K-δ inhibitors have shown impressive activity in lymphoid malignancies but have been hampered by autoimmune and infectious toxicities, leading to market withdrawals. We previously demonstrated activity of the PI3K-δγ inhibitor duvelisib in T cell lymphomas (TCLs) that was associated with inflammatory adverse events. As reported here, we conducted a phase 1b/2a study of duvelisib in combination with either romidepsin (n = 66) or bortezomib (n = 32) in patients with relapsed/refractory TCL and found that the addition of romidepsin, but not bortezomib, appeared to increase efficacy while attenuating PI3K inhibitor-driven toxicity. The primary endpoint of the study was to determine the safety and maximum tolerated dose of duvelisib, which was 75 mg twice daily when combined with romidepsin versus 25 mg twice daily when combined with bortezomib. The most common adverse events were neutropenia (42%, 25/59) and fatigue (37%, 22/59) in patients treated with duvelisib and romidepsin and diarrhea (48%, 11/23) and neutropenia (30%, 7/23) in patients treated with duvelisib and bortezomib. Duvelisib and romidepsin resulted in less grade 3/4 hepatotoxicity (14%, 8/59) compared to 40% (14/35) in our previous study with duvelisib monotherapy. This was associated with reductions in circulating inflammatory mediators and myeloid cell inflammatory gene expression. Secondary endpoints of overall and complete response rates were 55% (35/64) and 34% (22/64) for patients treated with duvelisib and romidepsin and 34% (11/32) and 13% (4/32) for patients treated with duvelisib and bortezomib. Among patients with peripheral T cell lymphomas (PTCLs), overall and complete response rates of duvelisib and romidepsin were 56% (27/48) and 44% (21/48), respectively, with exploratory analyses showing increased response rates in patients with a follicular helper T cell subtype. These findings support further development of combined PI3K and histone deacetylase (HDAC) inhibition in TCLs and suggest a unique strategy to enable PI3K inhibitor-based combinations for additional patient populations. ClinicalTrials.gov identifier: NCT02783625 .

@article{maliga_immune_2024,
  title = {Immune {Profiling} of {Dermatologic} {Adverse} {Events} from {Checkpoint} {Blockade} {Using} {Tissue} {Cyclic} {Immunofluorescence}: {A} {Pilot} {Study}},
  volume = {144},
  issn = {1523-1747},
  shorttitle = {Immune {Profiling} of {Dermatologic} {Adverse} {Events} from {Checkpoint} {Blockade} {Using} {Tissue} {Cyclic} {Immunofluorescence}},
  doi = {10.1016/j.jid.2024.01.024},
  language = {eng},
  number = {8},
  journal = {The Journal of Investigative Dermatology},
  author = {Maliga, Zoltan and Kim, Daniel Y. and Bui, Ai-Tram N. and Lin, Jia-Ren and Dewan, Anna K. and Jadeja, Saagar and Murphy, George F. and Nirmal, Ajit J. and Lian, Christine G. and Sorger, Peter K. and LeBoeuf, Nicole R.},
  month = aug,
  year = {2024},
  pmid = {38360200},
  pmcid = {PMC11447745},
  keywords = {Aged, Cutaneous adverse events, Drug Eruptions, Female, Fluorescent Antibody Technique, Humans, Immune checkpoint blockade, Immune Checkpoint Inhibitors, Immune-related adverse events, Immunotherapy, Male, Middle Aged, Pilot Projects, Skin, Tissue cyclic immunofluorescence},
  pages = {1887--1890.e5}
}

@article{nirmal_scimap_2024,
  title = {{SCIMAP}: {A} {Python} {Toolkit} for {Integrated} {Spatial} {Analysis} of {Multiplexed} {Imaging} {Data}},
  volume = {9},
  issn = {2475-9066},
  shorttitle = {{SCIMAP}},
  url = {https://joss.theoj.org/papers/10.21105/joss.06604},
  doi = {10.21105/joss.06604},
  language = {en},
  number = {97},
  urldate = {2024-05-29},
  journal = {Journal of Open Source Software},
  author = {Nirmal, Ajit J. and Sorger, Peter K.},
  month = may,
  year = {2024},
  pmid = {38873023},
  pmcid = {PMC11173324},
  pages = {6604},
  file = {Full Text PDF:/Users/aj/Zotero/storage/7A7E5TM2/Nirmal and Sorger - 2024 - SCIMAP A Python Toolkit for Integrated Spatial An.pdf:application/pdf}
}

Nirmal et al., (2024). SCIMAP: A Python Toolkit for Integrated Spatial Analysis of Multiplexed Imaging Data. Journal of Open Source Software, 9(97), 6604, https://doi.org/10.21105/joss.06604

@article{wan_spatialcells_2024,
  title = {{SpatialCells}: automated profiling of tumor microenvironments with spatially resolved multiplexed single-cell data},
  volume = {25},
  issn = {1477-4054},
  shorttitle = {{SpatialCells}},
  doi = {10.1093/bib/bbae189},
  language = {eng},
  number = {3},
  journal = {Briefings in Bioinformatics},
  author = {Wan, Guihong and Maliga, Zoltan and Yan, Boshen and Vallius, Tuulia and Shi, Yingxiao and Khattab, Sara and Chang, Crystal and Nirmal, Ajit J. and Yu, Kun-Hsing and Liu, David and Lian, Christine G. and DeSimone, Mia S. and Sorger, Peter K. and Semenov, Yevgeniy R.},
  month = mar,
  year = {2024},
  pmid = {38701421},
  pmcid = {PMC11066940},
  keywords = {Computational Biology, Humans, Machine Learning, multiplexed single-cell data, Neoplasms, region-based profiling, Single-Cell Analysis, Software, spatial analysis, spatial omics, tumor immune infiltration, tumor microenvironment, Tumor Microenvironment},
  pages = {bbae189},
  file = {Full Text:/Users/aj/Zotero/storage/57NBPT5F/Wan et al. - 2024 - SpatialCells automated profiling of tumor microenvironments with spatially resolved multiplexed sin.pdf:application/pdf}
}

Cancer is a complex cellular ecosystem where malignant cells coexist and interact with immune, stromal and other cells within the tumor microenvironment (TME). Recent technological advancements in spatially resolved multiplexed imaging at single-cell resolution have led to the generation of large-scale and high-dimensional datasets from biological specimens. This underscores the necessity for automated methodologies that can effectively characterize molecular, cellular and spatial properties of TMEs for various malignancies. This study introduces SpatialCells, an open-source software package designed for region-based exploratory analysis and comprehensive characterization of TMEs using multiplexed single-cell data. The source code and tutorials are available at https://semenovlab.github.io/SpatialCells. SpatialCells efficiently streamlines the automated extraction of features from multiplexed single-cell data and can process samples containing millions of cells. Thus, SpatialCells facilitates subsequent association analyses and machine learning predictions, making it an essential tool in advancing our understanding of tumor growth, invasion and metastasis.

@article{wan_development_2024,
  title = {Development and validation of time-to-event models to predict metastatic recurrence of localized cutaneous melanoma},
  volume = {90},
  issn = {1097-6787},
  doi = {10.1016/j.jaad.2023.08.105},
  language = {eng},
  number = {2},
  journal = {Journal of the American Academy of Dermatology},
  author = {Wan, Guihong and Leung, Bonnie W. and DeSimone, Mia S. and Nguyen, Nga and Rajeh, Ahmad and Collier, Michael R. and Rashdan, Hannah and Roster, Katie and Zhou, Xu and Moseley, Cameron B. and Nirmal, Ajit J. and Pelletier, Roxanne J. and Maliga, Zoltan and Marko-Varga, Gyorgy and Németh, István Balázs and Tsao, Hensin and Asgari, Maryam M. and Gusev, Alexander and Stagner, Anna M. and Lian, Christine G. and Hurlbert, Marc S. and Liu, Feng and Yu, Kun-Hsing and Sorger, Peter K. and Semenov, Yevgeniy R.},
  month = feb,
  year = {2024},
  pmid = {37797836},
  pmcid = {PMC10843255},
  keywords = {clinicopathologic factors, Humans, locoregional recurrence, Melanoma, metastatic recurrence, Neoplasm Recurrence, Local, Retrospective Studies, Skin Neoplasms, stage I/II melanoma, time-to-event prediction},
  pages = {288--298}
}

BACKGROUND: The recent expansion of immunotherapy for stage IIB/IIC melanoma highlights a growing clinical need to identify patients at high risk of metastatic recurrence and, therefore, most likely to benefit from this therapeutic modality.
OBJECTIVE: To develop time-to-event risk prediction models for melanoma metastatic recurrence.
METHODS: Patients diagnosed with stage I/II primary cutaneous melanoma between 2000 and 2020 at Mass General Brigham and Dana-Farber Cancer Institute were included. Melanoma recurrence date and type were determined by chart review. Thirty clinicopathologic factors were extracted from electronic health records. Three types of time-to-event machine-learning models were evaluated internally and externally in the distant versus locoregional/nonrecurrence prediction.
RESULTS: This study included 954 melanomas (155 distant, 163 locoregional, and 636 1:2 matched nonrecurrences). Distant recurrences were associated with worse survival compared to locoregional/nonrecurrences (HR: 6.21, P \textless .001) and to locoregional recurrences only (HR: 5.79, P \textless .001). The Gradient Boosting Survival model achieved the best performance (concordance index: 0.816; time-dependent AUC: 0.842; Brier score: 0.103) in the external validation.
LIMITATIONS: Retrospective nature and cohort from one geography.
CONCLUSIONS: These results suggest that time-to-event machine-learning models can reliably predict the metastatic recurrence from localized melanoma and help identify high-risk patients who are most likely to benefit from immunotherapy.

@article{wu_tp63_2023,
  title = {{TP63} fusions drive multicomplex enhancer rewiring, lymphomagenesis, and {EZH2} dependence},
  volume = {15},
  issn = {1946-6242},
  doi = {10.1126/scitranslmed.adi7244},
  language = {eng},
  number = {714},
  journal = {Science Translational Medicine},
  author = {Wu, Gongwei and Yoshida, Noriaki and Liu, Jihe and Zhang, Xiaoyang and Xiong, Yuan and Heavican-Foral, Tayla B. and Mandato, Elisa and Liu, Huiyun and Nelson, Geoffrey M. and Yang, Lu and Chen, Renee and Donovan, Katherine A. and Jones, Marcus K. and Roshal, Mikhail and Zhang, Yanming and Xu, Ran and Nirmal, Ajit J. and Jain, Salvia and Leahy, Catharine and Jones, Kristen L. and Stevenson, Kristen E. and Galasso, Natasha and Ganesan, Nivetha and Chang, Tiffany and Wu, Wen-Chao and Louissaint, Abner and Debaize, Lydie and Yoon, Hojong and Dal Cin, Paola and Chan, Wing C. and Ho Sui, Shannan J. and Ng, Samuel Y. and Feldman, Andrew L. and Horwitz, Steven M. and Adelman, Karen and Fischer, Eric S. and Chen, Chun-Wei and Weinstock, David M. and Brown, Myles},
  month = sep,
  year = {2023},
  pmid = {37729434},
  pmcid = {PMC11014717},
  keywords = {Animals, Cell Nucleus, Co-Repressor Proteins, Disease Models, Animal, Enhancer of Zeste Homolog 2 Protein, Humans, Mice, Oncogenes, Transcription Factors, Transcriptional Activation, Tumor Suppressor Proteins},
  pages = {eadi7244},
  file = {PubMed Central Full Text PDF:/Users/aj/Zotero/storage/4MCAALZM/Wu et al. - 2023 - TP63 fusions drive multicomplex enhancer rewiring, lymphomagenesis, and EZH2 dependence.pdf:application/pdf}
}

Gene fusions involving tumor protein p63 gene (TP63) occur in multiple T and B cell lymphomas and portend a dismal prognosis for patients. The function and mechanisms of TP63 fusions remain unclear, and there is no target therapy for patients with lymphoma harboring TP63 fusions. Here, we show that TP63 fusions act as bona fide oncogenes and are essential for fusion-positive lymphomas. Transgenic mice expressing TBL1XR1::TP63, the most common TP63 fusion, develop diverse lymphomas that recapitulate multiple human T and B cell lymphomas. Here, we identify that TP63 fusions coordinate the recruitment of two epigenetic modifying complexes, the nuclear receptor corepressor (NCoR)-histone deacetylase 3 (HDAC3) by the N-terminal TP63 fusion partner and the lysine methyltransferase 2D (KMT2D) by the C-terminal TP63 component, which are both required for fusion-dependent survival. TBL1XR1::TP63 localization at enhancers drives a unique cell state that involves up-regulation of MYC and the polycomb repressor complex 2 (PRC2) components EED and EZH2. Inhibiting EZH2 with the therapeutic agent valemetostat is highly effective at treating transgenic lymphoma murine models, xenografts, and patient-derived xenografts harboring TP63 fusions. One patient with TP63-rearranged lymphoma showed a rapid response to valemetostat treatment. In summary, TP63 fusions link partner components that, together, coordinate multiple epigenetic complexes, resulting in therapeutic vulnerability to EZH2 inhibition.

@article{gaglia_lymphocyte_2023,
  title = {Lymphocyte networks are dynamic cellular communities in the immunoregulatory landscape of lung adenocarcinoma},
  issn = {1878-3686},
  doi = {10.1016/j.ccell.2023.03.015},
  language = {eng},
  journal = {Cancer Cell},
  author = {Gaglia, Giorgio and Burger, Megan L. and Ritch, Cecily C. and Rammos, Danae and Dai, Yang and Crossland, Grace E. and Tavana, Sara Z. and Warchol, Simon and Jaeger, Alex M. and Naranjo, Santiago and Coy, Shannon and Nirmal, Ajit J. and Krueger, Robert and Lin, Jia-Ren and Pfister, Hanspeter and Sorger, Peter K. and Jacks, Tyler and Santagata, Sandro},
  month = apr,
  year = {2023},
  pmid = {37059105},
  keywords = {cancer vaccines, computational biology, CyCIF, immunotherapy, lung adenocarcinoma, multimodal data integration, multiplexed imaging, spatial biology, spatial profiling, systems biology, Humans, Animals, Mice, Immunotherapy, Lung Neoplasms, CD8-Positive T-Lymphocytes, Adenocarcinoma of Lung, Immunity},
  pages = {S1535--6108(23)00088--0},
  file = {Submitted Version:/Users/aj/Zotero/storage/A4Y42LBZ/Gaglia et al. - 2023 - Lymphocyte networks are dynamic cellular communiti.pdf:application/pdf}
}

Lymphocytes are key for immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. We used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of lung tumors from a Kras/Trp53-mutant mouse model and human resections. Networks of interacting lymphocytes ("lymphonets") emerged as a distinctive feature of the anti-cancer immune response. Lymphonets nucleated from small T cell clusters and incorporated B cells with increasing size. CXCR3-mediated trafficking modulated lymphonet size and number, but T cell antigen expression directed intratumoral localization. Lymphonets preferentially harbored TCF1+ PD-1+ progenitor CD8+ T cells involved in responses to immune checkpoint blockade (ICB) therapy. Upon treatment of mice with ICB or an antigen-targeted vaccine, lymphonets retained progenitor and gained cytotoxic CD8+ T cell populations, likely via progenitor differentiation. These data show that lymphonets create a spatial environment supportive of CD8+ T cell anti-tumor responses.

@article{gentles_single_2023,
  title = {Single {Cell} {Spatial} {Biology} for {Precision} {Cancer} {Medicine}},
  volume = {28},
  issn = {2335-6936},
  language = {eng},
  journal = {Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing},
  author = {Gentles, Andrew J. and Nirmal, Ajit J. and Heiser, Laura M. and Lundberg, Emma and Newman, Aaron M.},
  year = {2023},
  pmid = {36541010},
  keywords = {Biomarkers, Tumor, Computational Biology, Ecosystem, Humans, Neoplasms, Precision Medicine, Tumor Microenvironment},
  pages = {549--553}
}

In cancer, complex ecosystems of interacting cell types play fundamental roles in tumor development, progression, and response to therapy. However, the cellular organization, community structure, and spatially defined microenvironments of human tumors remain poorly understood. With the emergence of new technologies for high-throughput spatial profiling of complex tissue specimens, it is now possible to identify clinically significant spatial features with high granularity. In this PSB workshop, we will highlight recent advances in this area and explore how single cell spatial profiling can advance precision cancer medicine.

@article{mills_multiplexed_2022,
  title = {Multiplexed and reproducible high content screening of live and fixed cells using {Dye} {Drop}},
  volume = {13},
  issn = {2041-1723},
  doi = {10.1038/s41467-022-34536-7},
  language = {eng},
  number = {1},
  journal = {Nature Communications},
  author = {Mills, Caitlin E. and Subramanian, Kartik and Hafner, Marc and Niepel, Mario and Gerosa, Luca and Chung, Mirra and Victor, Chiara and Gaudio, Benjamin and Yapp, Clarence and Nirmal, Ajit J. and Clark, Nicholas and Sorger, Peter K.},
  month = nov,
  year = {2022},
  pmid = {36376301},
  pmcid = {PMC9663587},
  keywords = {Antineoplastic Agents, Cell Survival, Drug Discovery, High-Throughput Screening Assays, Microscopy, Staining and Labeling},
  pages = {6918}
}

High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g., CellTiter-Glo®). Here we describe a public domain Dye Drop method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.

@article{warchol_visinity_2022,
  title = {Visinity: {Visual} {Spatial} {Neighborhood} {Analysis} for {Multiplexed} {Tissue} {Imaging} {Data}},
  volume = {PP},
  issn = {1941-0506},
  shorttitle = {Visinity},
  doi = {10.1109/TVCG.2022.3209378},
  language = {eng},
  journal = {IEEE transactions on visualization and computer graphics},
  author = {Warchol, Simon and Krueger, Robert and Nirmal, Ajit Johnson and Gaglia, Giorgio and Jessup, Jared and Ritch, Cecily C. and Hoffer, John and Muhlich, Jeremy and Burger, Megan L. and Jacks, Tyler and Santagata, Sandro and Sorger, Peter K. and Pfister, Hanspeter},
  month = sep,
  year = {2022},
  pmid = {36170403}
}

New highly-multiplexed imaging technologies have enabled the study of tissues in unprecedented detail. These methods are increasingly being applied to understand how cancer cells and immune response change during tumor development, progression, and metastasis, as well as following treatment. Yet, existing analysis approaches focus on investigating small tissue samples on a per-cell ba- sis, not taking into account the spatial proximity of cells, which indicates cell-cell interaction and specific biological processes in the larger cancer microenvironment. We present Visinity, a scalable visual analytics system to analyze cell interaction patterns across cohorts of whole-slide multiplexed tissue images. Our approach is based on a fast regional neighborhood computation, leveraging unsupervised learning to quantify, compare, and group cells by their surrounding cellular neighborhood. These neighborhoods can be visually analyzed in an exploratory and confirmatory workflow. Users can explore spatial patterns present across tissues through a scalable image viewer and coordinated views highlighting the neighborhood composition and spatial arrangements of cells. To verify or refine existing hypothe- ses, users can query for specific patterns to determine their presence and statistical significance. Findings can be interactively anno- tated, ranked, and compared in the form of small multiples. In two case studies with biomedical experts, we demonstrate that Visinity can identify common biological processes within a human tonsil and uncover novel white-blood cell networks and immune-tumor interactions.

@article{nirmal_spatial_2022,
  title = {The {Spatial} {Landscape} of {Progression} and {Immunoediting} in {Primary} {Melanoma} at {Single}-{Cell} {Resolution}},
  volume = {12},
  issn = {2159-8290},
  doi = {10.1158/2159-8290.CD-21-1357},
  language = {eng},
  number = {6},
  journal = {Cancer Discovery},
  author = {Nirmal, Ajit J. and Maliga, Zoltan and Vallius, Tuulia and Quattrochi, Brian and Chen, Alyce A. and Jacobson, Connor A. and Pelletier, Roxanne J. and Yapp, Clarence and Arias-Camison, Raquel and Chen, Yu-An and Lian, Christine G. and Murphy, George F. and Santagata, Sandro and Sorger, Peter K.},
  month = jun,
  year = {2022},
  pmid = {35404441},
  pmcid = {PMC9167783},
  keywords = {Cytokines, Ecosystem, Humans, Melanoma, Skin Neoplasms},
  pages = {1518--1541},
  file = {Full Text:/Users/aj/Zotero/storage/N7ZP6NUH/Nirmal et al. - 2022 - The Spatial Landscape of Progression and Immunoedi.pdf:application/pdf;Full Text PDF:/Users/aj/Zotero/storage/NPFVJ8J8/Nirmal et al. - 2022 - The Spatial Landscape of Progression and Immunoedi.pdf:application/pdf;Snapshot:/Users/aj/Zotero/storage/9VX8ZHYQ/The-Spatial-Landscape-of-Progression-and.html:text/html}
}

Cutaneous melanoma is a highly immunogenic malignancy that is surgically curable at early stages but life-threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially resolved microregion transcriptomics to study immune evasion and immunoediting in primary melanoma. We find that recurrent cellular neighborhoods involving tumor, immune, and stromal cells change significantly along a progression axis involving precursor states, melanoma in situ, and invasive tumor. Hallmarks of immunosuppression are already detectable in precursor regions. When tumors become locally invasive, a consolidated and spatially restricted suppressive environment forms along the tumor-stromal boundary. This environment is established by cytokine gradients that promote expression of MHC-II and IDO1, and by PD1-PDL1-mediated cell contacts involving macrophages, dendritic cells, and T cells. A few millimeters away, cytotoxic T cells synapse with melanoma cells in fields of tumor regression. Thus, invasion and immunoediting can coexist within a few millimeters of each other in a single specimen.
SIGNIFICANCE: The reorganization of the tumor ecosystem in primary melanoma is an excellent setting in which to study immunoediting and immune evasion. Guided by classic histopathology, spatial profiling of proteins and mRNA reveals recurrent morphologic and molecular features of tumor evolution that involve localized paracrine cytokine signaling and direct cell-cell contact. This article is highlighted in the In This Issue feature, p. 1397.

@article{schapiro_mcmicro_2022,
  title = {{MCMICRO}: a scalable, modular image-processing pipeline for multiplexed tissue imaging},
  volume = {19},
  issn = {1548-7105},
  shorttitle = {{MCMICRO}},
  doi = {10.1038/s41592-021-01308-y},
  language = {eng},
  number = {3},
  journal = {Nature Methods},
  author = {Schapiro, Denis and Sokolov, Artem and Yapp, Clarence and Chen, Yu-An and Muhlich, Jeremy L. and Hess, Joshua and Creason, Allison L. and Nirmal, Ajit J. and Baker, Gregory J. and Nariya, Maulik K. and Lin, Jia-Ren and Maliga, Zoltan and Jacobson, Connor A. and Hodgman, Matthew W. and Ruokonen, Juha and Farhi, Samouil L. and Abbondanza, Domenic and McKinley, Eliot T. and Persson, Daniel and Betts, Courtney and Sivagnanam, Shamilene and Regev, Aviv and Goecks, Jeremy and Coffey, Robert J. and Coussens, Lisa M. and Santagata, Sandro and Sorger, Peter K.},
  month = mar,
  year = {2022},
  pmid = {34824477},
  pmcid = {PMC8916956},
  keywords = {Humans, Diagnostic Imaging, Image Processing, Computer-Assisted, Neoplasms, Software, Image processing, Systems biology},
  pages = {311--315},
  file = {Full Text:/Users/aj/Zotero/storage/LVW9VBMJ/Schapiro et al. - 2022 - MCMICRO a scalable, modular image-processing pipe.pdf:application/pdf;Full Text:/Users/aj/Zotero/storage/BY9XX4UA/Schapiro et al. - 2022 - MCMICRO a scalable, modular image-processing pipe.pdf:application/pdf;Full Text PDF:/Users/aj/Zotero/storage/4ASYQ4AL/Schapiro et al. - 2022 - MCMICRO a scalable, modular image-processing pipe.pdf:application/pdf}
}

Highly multiplexed tissue imaging makes detailed molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of large multichannel images poses a substantial computational challenge. Here, we describe a modular and open-source computational pipeline, MCMICRO, for performing the sequential steps needed to transform whole-slide images into single-cell data. We demonstrate the use of MCMICRO on tissue and tumor images acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

@article{schapiro_miti_2022,
  title = {{MITI} minimum information guidelines for highly multiplexed tissue images},
  volume = {19},
  copyright = {2022 Springer Nature America, Inc.},
  issn = {1548-7105},
  url = {https://www.nature.com/articles/s41592-022-01415-4},
  doi = {10.1038/s41592-022-01415-4},
  language = {en},
  number = {3},
  urldate = {2022-04-19},
  journal = {Nature Methods},
  author = {Schapiro, Denis and Yapp, Clarence and Sokolov, Artem and Reynolds, Sheila M. and Chen, Yu-An and Sudar, Damir and Xie, Yubin and Muhlich, Jeremy and Arias-Camison, Raquel and Arena, Sarah and Taylor, Adam J. and Nikolov, Milen and Tyler, Madison and Lin, Jia-Ren and Burlingame, Erik A. and Chang, Young H. and Farhi, Samouil L. and Thorsson, Vésteinn and Venkatamohan, Nithya and Drewes, Julia L. and Pe’er, Dana and Gutman, David A. and Herrmann, Markus D. and Gehlenborg, Nils and Bankhead, Peter and Roland, Joseph T. and Herndon, John M. and Snyder, Michael P. and Angelo, Michael and Nolan, Garry and Swedlow, Jason R. and Schultz, Nikolaus and Merrick, Daniel T. and Mazzili, Sarah A. and Cerami, Ethan and Rodig, Scott J. and Santagata, Sandro and Sorger, Peter K.},
  month = mar,
  year = {2022},
  note = {Number: 3
  Publisher: Nature Publishing Group},
  keywords = {Data publication and archiving, Databases, Image processing, Standards},
  pages = {262--267},
  file = {Snapshot:/Users/aj/Zotero/storage/AN7IFAWB/s41592-022-01415-4.html:text/html}
}

The imminent release of tissue atlases combining multichannel microscopy with single-cell sequencing and other omics data from normal and diseased specimens creates an urgent need for data and metadata standards to guide data deposition, curation and release. We describe a Minimum Information about Highly Multiplexed Tissue Imaging (MITI) standard that applies best practices developed for genomics and for other microscopy data to highly multiplexed tissue images and traditional histology.

@article{wu_overcoming_2021,
  title = {Overcoming {IMiD} {Resistance} in {T}-cell {Lymphomas} {Through} {Potent} {Degradation} of {ZFP91} and {IKZF1}},
  issn = {0006-4971},
  url = {https://doi.org/10.1182/blood.2021014701},
  doi = {10.1182/blood.2021014701},
  urldate = {2022-01-24},
  journal = {Blood},
  author = {Wu, Wenchao and Nelson, Geoffrey and Koch, Raphael and Donovan, Katherine Aleisha and Nowak, Radoslaw P and Heavican-Foral, Tayla B. and Nirmal, Ajit Johnson and Liu, Huiyun and Yang, Lei and Duffy, Jessica and Powers, Foster and Stevenson, Kristen E. and Jones, Marcus and Ng, Samuel Y. and Wu, Gongwei and Jain, Salvia and Xu, Ran and Amaka, Sam and Trevisani, Christopher and Donaldson, Nicholas and Hagner, Patrick Ryan and de Leval, Laurence and Gaulard, Philippe and Iqbal, Javeed and Thakurta, Anjan and Fischer, Eric S and Adelman, Karen and Weinstock, David M.},
  month = dec,
  year = {2021},
  keywords = {Humans, Drug Resistance, Neoplasm, Ikaros Transcription Factor, Immunologic Factors, Lenalidomide, Lymphoma, T-Cell, Multiple Myeloma, Thalidomide, Ubiquitin-Protein Ligases, Ubiquitination},
  pages = {blood.2021014701},
  file = {Snapshot:/Users/aj/Zotero/storage/58Y6QBVH/Overcoming-IMiD-Resistance-in-T-cell-Lymphomas.html:text/html}
}

Immunomodulatory (IMiD) agents like lenalidomide and pomalidomide induce the recruitment of IKZF1 and other targets to the CRL4CRBN E3 ubiquitin ligase, resulting in their ubiquitination and degradation. These agents are highly active in B-cell lymphomas and a subset of myeloid diseases but have compromised effects in T-cell lymphomas (TCLs). Here we show that two factors determine resistance to IMiDs among TCLs. First, limited CRBN expression reduces IMiD activity in TCLs but can be overcome by newer-generation degrader CC-92480. Using mass spectrometry, we show that CC-92480 selectively degrades IKZF1 and ZFP91 in TCL cells with greater potency than pomalidomide. As a result, CC-92480 is highly active against multiple TCL subtypes and showed greater efficacy than pomalidomide across 4 in vivo TCL models. Second, we demonstrate that ZFP91 functions as a bona fide transcription factor that co-regulates cell survival with IKZF1 in IMiD-resistant TCLs. By activating keynote genes from WNT, NF-kB, and MAP kinase signaling, ZFP91 directly promotes resistance to IKZF1 loss. Moreover, lenalidomide-sensitive TCLs can acquire stable resistance via ZFP91 rewiring, which involves casein kinase 2 (CK2) mediated c-Jun inactivation. Overall, these findings identify a critical transcription factor network within TCLs and provide clinical proof of concept for the novel therapy using next-generation degraders.

@article{kalocsay_multiplexed_2020,
  title = {Multiplexed proteomics and imaging of resolving and lethal {SARS}-{CoV}-2 infection in the lung},
  copyright = {© 2020, Posted by Cold Spring Harbor Laboratory. The copyright holder for this pre-print is the author. All rights reserved. The material may not be redistributed, re-used or adapted without the author's permission.},
  url = {https://www.biorxiv.org/content/10.1101/2020.10.14.339952v1},
  doi = {10.1101/2020.10.14.339952},
  language = {en},
  urldate = {2021-02-24},
  journal = {bioRxiv},
  author = {Kalocsay, Marian and Maliga, Zoltan and Nirmal, Ajit J. and Eisert, Robyn J. and Bradshaw, Gary A. and Solomon, Isaac H. and Chen, Yu-An and Pelletier, Roxanne J. and Jacobson, Connor A. and Mintseris, Julian and Padera, Robert F. and Martinot, Amanda J. and Barouch, Dan H. and Santagata, Sandro and Sorger, Peter K.},
  month = oct,
  year = {2020},
  note = {Publisher: Cold Spring Harbor Laboratory
  Section: New Results},
  pages = {2020.10.14.339952},
  file = {Snapshot:/Users/aj/Zotero/storage/YWNZX5VF/2020.10.14.html:text/html}
}

\textlessh3\textgreaterABSTRACT\textless/h3\textgreater \textlessp\textgreaterNormal tissue physiology and repair depends on communication with the immune system. Understanding this communication at the molecular level in intact tissue requires new methods. The consequences of SARS-CoV-2 infection, which can result in acute respiratory distress, thrombosis and death, has been studied primarily in accessible liquid specimens such as blood, sputum and bronchoalveolar lavage, all of which are peripheral to the primary site of infection in the lung. Here, we describe the combined use of multiplexed deep proteomics with multiplexed imaging to profile infection and its sequelae directly in fixed lung tissue specimens obtained from necropsy of infected animals and autopsy of human decedents. We characterize multiple steps in disease response from cytokine accumulation and protein phosphorylation to activation of receptors, changes in signaling pathways, and crosslinking of fibrin to form clots. Our data reveal significant differences between naturally resolving SARS-CoV-2 infection in rhesus macaques and lethal COVID-19 in humans. The approach we describe is broadly applicable to other tissues and diseases.\textless/p\textgreater\textlessh3\textgreaterSummary\textless/h3\textgreater \textlessp\textgreaterProteomics of infected tissue reveals differences in inflammatory and thrombotic responses between resolving and lethal COVID-19.\textless/p\textgreater

@article{rozenblatt-rosen_human_2020,
  title = {The {Human} {Tumor} {Atlas} {Network}: {Charting} {Tumor} {Transitions} across {Space} and {Time} at {Single}-{Cell} {Resolution}},
  volume = {181},
  copyright = {All rights reserved},
  issn = {1097-4172},
  shorttitle = {The {Human} {Tumor} {Atlas} {Network}},
  doi = {10.1016/j.cell.2020.03.053},
  language = {eng},
  number = {2},
  journal = {Cell},
  author = {Rozenblatt-Rosen, Orit and Regev, Aviv and Oberdoerffer, Philipp and Nawy, Tal and Hupalowska, Anna and Rood, Jennifer E. and Ashenberg, Orr and Cerami, Ethan and Coffey, Robert J. and Demir, Emek and Ding, Li and Esplin, Edward D. and Ford, James M. and Goecks, Jeremy and Ghosh, Sharmistha and Gray, Joe W. and Guinney, Justin and Hanlon, Sean E. and Hughes, Shannon K. and Hwang, E. Shelley and Iacobuzio-Donahue, Christine A. and Jané-Valbuena, Judit and Johnson, Bruce E. and Lau, Ken S. and Lively, Tracy and Mazzilli, Sarah A. and Pe'er, Dana and Santagata, Sandro and Shalek, Alex K. and Schapiro, Denis and Snyder, Michael P. and Sorger, Peter K. and Spira, Avrum E. and Srivastava, Sudhir and Tan, Kai and West, Robert B. and Williams, Elizabeth H. and {Human Tumor Atlas Network}},
  month = apr,
  year = {2020},
  pmid = {32302568},
  pmcid = {PMC7376497},
  keywords = {Humans, Neoplasms, Single-Cell Analysis, Tumor Microenvironment, Genomics, metastasis, AI, Atlases as Topic, Cancer Moonshot, cancer transitions, Cell Transformation, Neoplastic, data integration, data visualization, Human Tumor Atlas, pre-cancer, Precision Medicine, resistance, single-cell genomics, spatial genomics, spatial imaging, tumor},
  pages = {236--249},
  file = {Full Text:/Users/aj/Zotero/storage/NQDELS58/Rozenblatt-Rosen et al. - 2020 - The Human Tumor Atlas Network Charting Tumor Tran.pdf:application/pdf}
}

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.

@article{sandercock_transcriptomics_2019,
  title = {Transcriptomics {Analysis} of {Porcine} {Caudal} {Dorsal} {Root} {Ganglia} in {Tail} {Amputated} {Pigs} {Shows} {Long}-{Term} {Effects} on {Many} {Pain}-{Associated} {Genes}},
  volume = {6},
  copyright = {All rights reserved},
  issn = {2297-1769},
  doi = {10.3389/fvets.2019.00314},
  language = {eng},
  journal = {Frontiers in Veterinary Science},
  author = {Sandercock, Dale A. and Barnett, Mark W. and Coe, Jennifer E. and Downing, Alison C. and Nirmal, Ajit J. and Di Giminiani, Pierpaolo and Edwards, Sandra A. and Freeman, Tom C.},
  year = {2019},
  pmid = {31620455},
  pmcid = {PMC6760028},
  keywords = {gene expression, animal welfare, inflammatory pain, neuropathic pain, pig, tail amputation, tail docking},
  pages = {314}
}

Tail amputation by tail docking or as an extreme consequence of tail biting in commercial pig production potentially has serious implications for animal welfare. Tail amputation causes peripheral nerve injury that might be associated with lasting chronic pain. The aim of this study was to investigate the short- and long-term effects of tail amputation in pigs on caudal DRG gene expression at different stages of development, particularly in relation to genes associated with nociception and pain. Microarrays were used to analyse whole DRG transcriptomes from tail amputated and sham-treated pigs 1, 8, and 16 weeks following tail treatment at either 3 or 63 days of age (8 pigs/treatment/age/time after treatment; n = 96). Tail amputation induced marked changes in gene expression (up and down) compared to sham-treated intact controls for all treatment ages and time points after tail treatment. Sustained changes in gene expression in tail amputated pigs were still evident 4 months after tail injury. Gene correlation network analysis revealed two co-expression clusters associated with amputation: Cluster A (759 down-regulated) and Cluster B (273 up-regulated) genes. Gene ontology (GO) enrichment analysis identified 124 genes in Cluster A and 61 genes in Cluster B associated with both "inflammatory pain" and "neuropathic pain." In Cluster A, gene family members of ion channels e.g., voltage-gated potassium channels (VGPC) and receptors e.g., GABA receptors, were significantly down-regulated compared to shams, both of which are linked to increased peripheral nerve excitability after axotomy. Up-regulated gene families in Cluster B were linked to transcriptional regulation, inflammation, tissue remodeling, and regulatory neuropeptide activity. These findings, demonstrate that tail amputation causes sustained transcriptomic expression changes in caudal DRG cells involved in inflammatory and neuropathic pain pathways.

@article{lee_durable_2018,
  title = {Durable engraftment of genetically modified {FVIII}-secreting autologous bone marrow stromal cells in the intramedullary microenvironment},
  volume = {22},
  copyright = {All rights reserved},
  issn = {1582-4934},
  doi = {10.1111/jcmm.13648},
  language = {eng},
  number = {7},
  journal = {Journal of Cellular and Molecular Medicine},
  author = {Lee, Sze Sing and Sivalingam, Jaichandran and Nirmal, Ajit J. and Ng, Wai Har and Kee, Irene and Song, In Chin and Kiong, Chin Yong and Gales, Kristoffer A. and Chua, Frederic and Pena, Edgar M. and Ogden, Bryan E. and Kon, Oi Lian},
  month = jul,
  year = {2018},
  pmid = {29682884},
  pmcid = {PMC6010829},
  keywords = {Animals, Male, Animals, Genetically Modified, autologous stem cell transplantation, Bone Marrow Cells, bone marrow stromal cells, cell therapy, Dogs, engraftment, factor VIII, Factor VIII, gene targeting, haemophilia A, Mesenchymal Stem Cell Transplantation, Mesenchymal Stem Cells, Muscle, Skeletal, Recombinant Proteins, tissue microenvironment, Zinc Finger Nucleases},
  pages = {3698--3702}
}

Genetically modified FVIII-expressing autologous bone marrow-derived mesenchymal stromal cells (BMSCs) could cure haemophilia A. However, culture-expanded BMSCs engraft poorly in extramedullary sites. Here, we compared the intramedullary cavity, skeletal muscle, subcutaneous tissue and systemic circulation as tissue microenvironments that could support durable engraftment of FVIII-secreting BMSC in vivo. A zinc finger nuclease integrated human FVIII transgene into PPP1R12C (intron 1) of culture-expanded primary canine BMSCs. FVIII-secretory capacity of implanted BMSCs in each dog was expressed as an individualized therapy index (number of viable BMSCs implanted × FVIII activity secreted/million BMSCs/24 hours). Plasma samples before and after implantation were assayed for transgenic FVIII protein using an anti-human FVIII antibody having negligible cross-reactivity with canine FVIII. Plasma transgenic FVIII persisted for at least 48 weeks after implantation in the intramedullary cavity. Transgenic FVIII protein levels were low after intramuscular implantation and undetectable after both intravenous infusion and subcutaneous implantation. All plasma samples were negative for anti-human FVIII antibodies. Plasma concentrations and durability of transgenic FVIII secretion showed no correlation with the therapy index. Thus, the implantation site microenvironment is crucial. The intramedullary microenvironment, but not extramedullary tissues, supported durable engraftment of genetically modified autologous FVIII-secreting BMSCs.

@article{pearce_continuous_2018,
  title = {Continuous {Biomarker} {Assessment} by {Exhaustive} {Survival} {Analysis}},
  copyright = {© 2018, Posted by Cold Spring Harbor Laboratory. This pre-print is available under a Creative Commons License (Attribution-NonCommercial-NoDerivs 4.0 International), CC BY-NC-ND 4.0, as described at http://creativecommons.org/licenses/by-nc-nd/4.0/},
  url = {https://www.biorxiv.org/content/10.1101/208660v2},
  doi = {10.1101/208660},
  language = {en},
  urldate = {2021-02-24},
  journal = {bioRxiv},
  author = {Pearce, Dominic A. and Nirmal, Ajit J. and Freeman, Tom C. and Sims, Andrew H.},
  month = mar,
  year = {2018},
  note = {Publisher: Cold Spring Harbor Laboratory
  Section: New Results},
  pages = {208660},
  file = {Snapshot:/Users/aj/Zotero/storage/FB6QLRZV/208660v2.html:text/html}
}

\textlessh3\textgreaterAbstract\textless/h3\textgreater \textlessp\textgreaterPublicly available high-throughput molecular data can enable biomarker identification and evaluation in a meta-analysis. However, a continuous biomarker’s underlying distribution and/or potential confounding factors associated with outcome will inevitably vary between cohorts and is often ignored. The survivALL R package (https://CRAN.R-project.org/package=survivALL) allows researchers to generate visual and numerical comparisons of all possible points-of-separation, enabling quantitative biomarkers to be reliably evaluated within and across datasets, independent of compositional variation. Here, we demonstrate survivALL’s ability to robustly and reproducibly determine an applicable level of gene expression for patient prognostic classification, in datasets of similar and dissimilar compositions. We believe survivALL represents a significant improvement over existing methodologies in stratifying patients and determining quantitative biomarker(s) cut-points for public and novel datasets.\textless/p\textgreater

@article{pridans_macrophage_2018,
  title = {Macrophage colony-stimulating factor increases hepatic macrophage content, liver growth, and lipid accumulation in neonatal rats},
  volume = {314},
  copyright = {All rights reserved},
  issn = {1522-1547},
  doi = {10.1152/ajpgi.00343.2017},
  language = {eng},
  number = {3},
  journal = {American Journal of Physiology. Gastrointestinal and Liver Physiology},
  author = {Pridans, Clare and Sauter, Kristin A. and Irvine, Katharine M. and Davis, Gemma M. and Lefevre, Lucas and Raper, Anna and Rojo, Rocio and Nirmal, Ajit J. and Beard, Philippa and Cheeseman, Michael and Hume, David A.},
  month = mar,
  year = {2018},
  pmid = {29351395},
  pmcid = {PMC5899243},
  keywords = {Female, Signal Transduction, Animals, Cell Proliferation, Male, Adiposity, Animals, Newborn, Birth Weight, Cells, Cultured, CSF1, CSF1R, Dexamethasone, Disease Models, Animal, Fatty Liver, Fetal Growth Retardation, Kupffer cells, Kupffer Cells, Lipid Metabolism, Liver, M-CSF, Macrophage Colony-Stimulating Factor, myeloid, Pregnancy, Rats, Sprague-Dawley, Receptors, Granulocyte-Macrophage Colony-Stimulating Factor, Spleen, Sus scrofa},
  pages = {G388--G398}
}

Signaling via the colony-stimulating factor 1 receptor (CSF1R) controls the survival, differentiation, and proliferation of macrophages. Mutations in CSF1 or CSF1R in mice and rats have pleiotropic effects on postnatal somatic growth. We tested the possible application of pig CSF1-Fc fusion protein as a therapy for low birth weight (LBW) at term, using a model based on maternal dexamethasone treatment in rats. Neonatal CSF1-Fc treatment did not alter somatic growth and did not increase the blood monocyte count. Instead, there was a substantial increase in the size of liver in both control and LBW rats, and the treatment greatly exacerbated lipid droplet accumulation seen in the dexamethasone LBW model. These effects were reversed upon cessation of treatment. Transcriptional profiling of the livers supported histochemical evidence of a large increase in macrophages with a resident Kupffer cell phenotype and revealed increased expression of many genes implicated in lipid droplet formation. There was no further increase in hepatocyte proliferation over the already high rates in neonatal liver. In conclusion, treatment of neonatal rats with CSF1-Fc caused an increase in liver size and hepatic lipid accumulation, due to Kupffer cell expansion and/or activation rather than hepatocyte proliferation. Increased liver macrophage numbers and expression of endocytic receptors could mitigate defective clearance functions in neonates. NEW & NOTEWORTHY This study is based on extensive studies in mice and pigs of the role of CSF1/CSF1R in macrophage development and postnatal growth. We extended the study to neonatal rats as a possible therapy for low birth weight. Unlike our previous studies in mice and pigs, there was no increase in hepatocyte proliferation and no increase in monocyte numbers. Instead, neonatal rats treated with CSF1 displayed reversible hepatic steatosis and Kupffer cell expansion.

@article{nirmal_immune_2018,
  title = {Immune {Cell} {Gene} {Signatures} for {Profiling} the {Microenvironment} of {Solid} {Tumors}},
  volume = {6},
  issn = {2326-6074},
  doi = {10.1158/2326-6066.CIR-18-0342},
  language = {eng},
  number = {11},
  journal = {Cancer Immunology Research},
  author = {Nirmal, Ajit J. and Regan, Tim and Shih, Barbara B. and Hume, David A. and Sims, Andrew H. and Freeman, Tom C.},
  year = {2018},
  pmid = {30266715},
  keywords = {Humans, Melanoma, Neoplasms, Single-Cell Analysis, Reproducibility of Results, Tumor Microenvironment, Transcriptome, Gene Expression Profiling, Biomarkers, Tumor, Trachoma},
  pages = {1388--1400},
  file = {Snapshot:/Users/aj/Zotero/storage/LJMJD72S/1388.html:text/html}
}

The immune composition of the tumor microenvironment regulates processes including angiogenesis, metastasis, and the response to drugs or immunotherapy. To facilitate the characterization of the immune component of tumors from transcriptomics data, a number of immune cell transcriptome signatures have been reported that are made up of lists of marker genes indicative of the presence a given immune cell population. The majority of these gene signatures have been defined through analysis of isolated blood cells. However, blood cells do not reflect the differentiation or activation state of similar cells within tissues, including tumors, and consequently markers derived from blood cells do not necessarily transfer well to tissues. To address this issue, we generated a set of immune gene signatures derived directly from tissue transcriptomics data using a network-based deconvolution approach. We define markers for seven immune cell types, collectively named ImSig, and demonstrate how these markers can be used for the quantitative estimation of the immune cell content of tumor and nontumor tissue samples. The utility of ImSig is demonstrated through the stratification of melanoma patients into subgroups of prognostic significance and the identification of immune cells with the use of single-cell RNA-sequencing data derived from tumors. Use of ImSig is facilitated by an R package (imsig). Cancer Immunol Res; 6(11); 1388-400. ©2018 AACR.

@article{shih_derivation_2017,
  title = {Derivation of marker gene signatures from human skin and their use in the interpretation of the transcriptional changes associated with dermatological disorders},
  volume = {241},
  issn = {1096-9896},
  doi = {10.1002/path.4864},
  language = {eng},
  number = {5},
  journal = {The Journal of Pathology},
  author = {Shih, Barbara B. and Nirmal, Ajit J. and Headon, Denis J. and Akbar, Arne N. and Mabbott, Neil A. and Freeman, Tom C.},
  year = {2017},
  pmcid = {PMC5363360},
  keywords = {Humans, Female, Transcriptome, Gene Expression Profiling, Age Factors, Aged, apocrine gland, Apocrine Glands, Cluster Analysis, gene expression, Gene Expression Regulation, Genetic Markers, Hair Follicle, Keratinocytes, Male, Melanocytes, Middle Aged, Oligonucleotide Array Sequence Analysis, psoriasis, Psoriasis, sebaceous gland, Sebaceous Glands, skin, Skin, sweat gland, Sweat Glands, transcriptomics},
  pages = {600--613}
}

Numerous studies have explored the altered transcriptional landscape associated with skin diseases to understand the nature of these disorders. However, data interpretation represents a significant challenge due to a lack of good maker sets for many of the specialized cell types that make up this tissue, whose composition may fundamentally alter during disease. Here we have sought to derive expression signatures that define the various cell types and structures that make up human skin, and demonstrate how they can be used to aid the interpretation of transcriptomic data derived from this organ. Two large normal skin transcriptomic datasets were identified, one RNA-seq (n = 578), the other microarray (n = 165), quality controlled and subjected separately to network-based analyses to identify clusters of robustly co-expressed genes. The biological significance of these clusters was then assigned using a combination of bioinformatics analyses, literature, and expert review. After cross comparison between analyses, 20 gene signatures were defined. These included expression signatures for hair follicles, glands (sebaceous, sweat, apocrine), keratinocytes, melanocytes, endothelia, muscle, adipocytes, immune cells, and a number of pathway systems. Collectively, we have named this resource SkinSig. SkinSig was then used in the analysis of transcriptomic datasets for 18 skin conditions, providing in-context interpretation of these data. For instance, conventional analysis has shown there to be a decrease in keratinization and fatty metabolism with age; we more accurately define these changes to be due to loss of hair follicles and sebaceous glands. SkinSig also highlighted the over-/under-representation of various cell types in skin diseases, reflecting an influx in immune cells in inflammatory disorders and a relative reduction in other cell types. Overall, our analyses demonstrate the value of this new resource in defining the functional profile of skin cell types and appendages, and in improving the interpretation of disease data. © 2016 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

@article{sivalingam_multidimensional_2016,
  title = {Multidimensional {Genome}-wide {Analyses} {Show} {Accurate} {FVIII} {Integration} by {ZFN} in {Primary} {Human} {Cells}},
  volume = {24},
  copyright = {All rights reserved},
  issn = {1525-0024},
  doi = {10.1038/mt.2015.223},
  language = {eng},
  number = {3},
  journal = {Molecular Therapy: The Journal of the American Society of Gene Therapy},
  author = {Sivalingam, Jaichandran and Kenanov, Dimitar and Han, Hao and Nirmal, Ajit Johnson and Ng, Wai Har and Lee, Sze Sing and Masilamani, Jeyakumar and Phan, Toan Thang and Maurer-Stroh, Sebastian and Kon, Oi Lian},
  month = mar,
  year = {2016},
  pmid = {26689265},
  pmcid = {PMC4786920},
  keywords = {Humans, Factor VIII, Binding Sites, Endonucleases, Gene Expression, Gene Targeting, Gene Transfer Techniques, Genetic Vectors, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, K562 Cells, Mutagenesis, Insertional, Protein Binding, Transgenes, Zinc Fingers},
  pages = {607--619}
}

Costly coagulation factor VIII (FVIII) replacement therapy is a barrier to optimal clinical management of hemophilia A. Therapy using FVIII-secreting autologous primary cells is potentially efficacious and more affordable. Zinc finger nucleases (ZFN) mediate transgene integration into the AAVS1 locus but comprehensive evaluation of off-target genome effects is currently lacking. In light of serious adverse effects in clinical trials which employed genome-integrating viral vectors, this study evaluated potential genotoxicity of ZFN-mediated transgenesis using different techniques. We employed deep sequencing of predicted off-target sites, copy number analysis, whole-genome sequencing, and RNA-seq in primary human umbilical cord-lining epithelial cells (CLECs) with AAVS1 ZFN-mediated FVIII transgene integration. We combined molecular features to enhance the accuracy and activity of ZFN-mediated transgenesis. Our data showed a low frequency of ZFN-associated indels, no detectable off-target transgene integrations or chromosomal rearrangements. ZFN-modified CLECs had very few dysregulated transcripts and no evidence of activated oncogenic pathways. We also showed AAVS1 ZFN activity and durable FVIII transgene secretion in primary human dermal fibroblasts, bone marrow- and adipose tissue-derived stromal cells. Our study suggests that, with close attention to the molecular design of genome-modifying constructs, AAVS1 ZFN-mediated FVIII integration in several primary human cell types may be safe and efficacious.

@article{krishnan_cell-cycle_2013,
  title = {Cell-cycle analysis and micronuclei frequency reveals {G0}/{G1} blockers as weak micronuclei inducers},
  volume = {36},
  copyright = {All rights reserved},
  issn = {1525-6014},
  doi = {10.3109/01480545.2012.737803},
  language = {eng},
  number = {2},
  journal = {Drug and Chemical Toxicology},
  author = {Krishnan, Anand and Gopinath, Vivek R. and Johnson, Ajit and Nair, S. Asha and Pillai, M. Radhakrishna},
  month = apr,
  year = {2013},
  pmid = {23126466},
  keywords = {Humans, Antineoplastic Agents, Cell Cycle, Cell Line, Tumor, G1 Phase, Leukocytes, Mononuclear, Micronuclei, Chromosome-Defective, Resting Phase, Cell Cycle},
  pages = {249--254}
}

Micronuclei (MN) formation is generally attributed to error in DNA synthesis or mitosis, which are represented by the S or G(2)/M phase respectively, in the cell-cycle histogram. Interestingly, many of the known anticancer drugs target these cell-cycle phases to elicit cytotoxicity. Here, we attempted to identify whether any correlation exists between the cell-cycle effect and MN induction potential using various treatments. In addition, we tracked down MN in cycling cells to assess its final fate. We treated SiHa cells with various known drugs and correlated their effects on cell-cycle and MN frequency. MN-tracking studies were performed in peripheral mononuclear and siHa cells upon staining with Giemsa and ethidium bromide respectively. We observed MN induction by all the tested drugs irrespective of their basic effect on cell cycle. However, MN induction was more with drugs which interfere with the S or G(2)/M than the G(0)/G(1) phase. Our results indicate G(0)/G(1) blockers to be comparatively safer drugs. Additionally, our results show that expulsion out of cells may be one of the main fates of drug-induced MN.

@article{bartnik_peptide_2012,
  title = {Peptide {Vaccine} {Therapy} in {Colorectal} {Cancer}},
  volume = {1},
  copyright = {All rights reserved},
  issn = {2076-393X},
  doi = {10.3390/vaccines1010001},
  language = {eng},
  number = {1},
  journal = {Vaccines},
  author = {Bartnik, Aleksandra and Nirmal, Ajit Johnson and Yang, Shi-Yu},
  month = aug,
  year = {2012},
  pmid = {26343847},
  pmcid = {PMC4552199},
  keywords = {colorectal cancer, CEA and MUC-1, EphA2, peptide vaccine therapy, SART3, survivin},
  pages = {1--16}
}

Colorectal cancer is the third most common cause of cancer-related deaths and the second most prevalent (after breast cancer) in the western world. High metastatic relapse rates and severe side effects associated with the adjuvant treatment have urged oncologists and clinicians to find a novel, less toxic therapeutic strategy. Considering the limited success of the past clinical trials involving peptide vaccine therapy to treat colorectal cancer, it is necessary to revise our knowledge of the immune system and its potential use in tackling cancer. This review presents the efforts of the scientific community in the development of peptide vaccine therapy for colorectal cancer. We review recent clinical trials and the strategies for immunologic monitoring of responses to peptide vaccine therapy. We also discuss the mechanisms underlying the therapy and potential molecular targets in colon cancer.