Higher labor intensity in US automotive assembly plants after transitioning to electric vehicles.

It has been widely suggested that the transition to battery electric vehicles will require 30% fewer assembly workers than those needed for internal combustion engine vehicles. Here, we use publicly available datasets on vehicle production and employment to show that labor intensity has increased at U.S. vehicle assembly plants that have fully transitioned to assembling battery electric vehicles. During the production ramp-up period, labor intensity increases by more than ten-fold compared to historic combustion vehicle assembly labor intensity. For one assembly site studied, labor intensity and total employment remained three times higher after a decade of electric vehicle production. Our study suggests that it may take longer than 15 years for electric vehicle assembly sites to achieve labor intensity parity with internal combustion vehicle assembly. Thus, rapid widespread loss of employment at vehicle assembly plants is a smaller risk than many fear. Moreover, our study calls for more regionally focused analyses of the transition's effects on labor using data-driven and macro-level surveying approaches.

Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma.

Histological transformation of follicular lymphoma (FL) to aggressive forms is associated with poor outcome. Phenotypic consequences of this evolution and its impact on the tumor microenvironment (TME) remain unknown. We perform single-cell whole genome sequencing (scWGS) and transcriptome sequencing (scWTS) of 11 paired pre/post-transformation patient samples and scWTS of additional samples from patients without transformation. Our analysis reveals evolutionary dynamics of transformation at single-cell resolution, highlighting a shifting TME landscape, with an emerging immune-cell exhaustion signature, co-evolving with the shifting malignant B phenotype in a regulatory ecosystem. Integration of scWGS and scWTS identifies malignant cell pathways upregulated during clonal tumor evolution. Using multi-color immunofluorescence, we transfer these findings to a TME-based transformation biomarker, subsequently validated in two independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation and shifting crosstalk between malignant cells and the TME.

Motive and opportunity: MYC rearrangements in high-grade B-cell lymphoma with MYC and BCL2 rearrangements (an LLMPP study).

ABSTRACT: Rearrangements that place the oncogenes MYC, BCL2, or BCL6 adjacent to superenhancers are common in mature B-cell lymphomas. Lymphomas with diffuse large B-cell lymphoma (DLBCL) or high-grade morphology with both MYC and BCL2 rearrangements are classified as high-grade B-cell lymphoma with MYC and BCL2 rearrangements ("double hit"; HGBCL-DH-BCL2) and are associated with aggressive disease and poor outcomes. Although it is established that MYC rearrangements involving immunoglobulin (IG) loci are associated with inferior outcomes relative to those involving other non-IG superenhancers, the frequency of and mechanisms driving IG vs non-IG MYC rearrangements have not been elucidated. Here, we used custom targeted capture and/or whole-genome sequencing to characterize oncogene rearrangements across 883 mature B-cell lymphomas including Burkitt lymphoma, follicular lymphoma, DLBCL, and HGBCL-DH-BCL2 tumors. We demonstrate that, although BCL2 rearrangement topology is consistent across entities, HGBCL-DH-BCL2 have distinct MYC rearrangement architecture relative to tumors with single MYC rearrangements or with both MYC and BCL6 rearrangements (HGBCL-DH-BCL6), including both a higher frequency of non-IG rearrangements and different architecture of MYC::IGH rearrangements. The distinct MYC rearrangement patterns in HGBCL-DH-BCL2 occur on the background of high levels of somatic hypermutation across MYC partner loci in HGBCL-DH-BCL2, creating more opportunity to form these rearrangements. Furthermore, because 1 IGH allele is already disrupted by the existing BCL2 rearrangement, the MYC rearrangement architecture in HGBCL-DH-BCL2 likely reflects selective pressure to preserve both BCL2 and B-cell receptor expression. These data provide new mechanistic explanations for the distinct patterns of MYC rearrangements observed across different lymphoma entities.

ARID1A orchestrates SWI/SNF-mediated sequential binding of transcription factors with ARID1A loss driving pre-memory B cell fate and lymphomagenesis.

ARID1A, a subunit of the canonical BAF nucleosome remodeling complex, is commonly mutated in lymphomas. We show that ARID1A orchestrates B cell fate during the germinal center (GC) response, facilitating cooperative and sequential binding of PU.1 and NF-kB at crucial genes for cytokine and CD40 signaling. The absence of ARID1A tilts GC cell fate toward immature IgM+CD80-PD-L2- memory B cells, known for their potential to re-enter new GCs. When combined with BCL2 oncogene, ARID1A haploinsufficiency hastens the progression of aggressive follicular lymphomas (FLs) in mice. Patients with FL with ARID1A-inactivating mutations preferentially display an immature memory B cell-like state with increased transformation risk to aggressive disease. These observations offer mechanistic understanding into the emergence of both indolent and aggressive ARID1A-mutant lymphomas through the formation of immature memory-like clonal precursors. Lastly, we demonstrate that ARID1A mutation induces synthetic lethality to SMARCA2/4 inhibition, paving the way for potential precision therapy for high-risk patients.

MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.

Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but has yet to be widely adopted for this application. To explore this, we trained single cell XGBoost classifiers from 98 diagnostic AML cell populations and 30 MRD negative samples. Performance was assessed by cross-validation. Predictions were integrated with UMAP as a heatmap parameter for an augmented/interactive AML MRD analysis framework, which was benchmarked against traditional MRD analysis for 25 test cases. The results showed that XGBoost achieved a median AUC of 0.97, effectively distinguishing diverse AML cell populations from normal cells. When integrated with UMAP, the classifiers highlighted MRD populations against the background of normal events. Our pipeline, MAGIC-DR, incorporated classifier predictions and UMAP into flow cytometry standard (FCS) files. This enabled a human-in-the-loop machine learning guided MRD workflow. Validation against conventional analysis for 25 MRD samples showed 100% concordance in myeloid blast detection, with MAGIC-DR also identifying several immature monocytic populations not readily found by conventional analysis. In conclusion, Integrating a supervised classifier with unsupervised dimension reduction offers a robust method for AML MRD analysis that can be seamlessly integrated into conventional workflows. Our approach can support and augment human analysis by highlighting abnormal populations that can be gated on for quantification and further assessment. This has the potential to speed up MRD analysis, and potentially improve detection sensitivity for certain AML immunophenotypes.

Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma.

PURPOSE: About a third of patients with relapsed or refractory classic Hodgkin lymphoma (r/r CHL) succumb to their disease after high-dose chemotherapy followed by autologous stem-cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL. PATIENTS AND METHODS: We performed imaging mass cytometry (IMC) on 71 paired primary diagnostic and relapse biopsies using a marker panel specific to CHL biology. For each cell type in the TME, we calculated a spatial score measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within the close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes. RESULTS: Highly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early r/r CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single-cell RNA sequencing data identified unique architecture defined by CXCR5+ Hodgkin and Reed Sternberg (HRS) cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay (RHL4S) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, CD68+ tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk versus low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay. CONCLUSION: We identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.

SpatialSort: a Bayesian model for clustering and cell population annotation of spatial proteomics data.

MOTIVATION: Recent advances in spatial proteomics technologies have enabled the profiling of dozens of proteins in thousands of single cells in situ. This has created the opportunity to move beyond quantifying the composition of cell types in tissue, and instead probe the spatial relationships between cells. However, most current methods for clustering data from these assays only consider the expression values of cells and ignore the spatial context. Furthermore, existing approaches do not account for prior information about the expected cell populations in a sample. RESULTS: To address these shortcomings, we developed SpatialSort, a spatially aware Bayesian clustering approach that allows for the incorporation of prior biological knowledge. Our method is able to account for the affinities of cells of different types to neighbour in space, and by incorporating prior information about expected cell populations, it is able to simultaneously improve clustering accuracy and perform automated annotation of clusters. Using synthetic and real data, we show that by using spatial and prior information SpatialSort improves clustering accuracy. We also demonstrate how SpatialSort can perform label transfer between spatial and nonspatial modalities through the analysis of a real world diffuse large B-cell lymphoma dataset. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at: https://github.com/Roth-Lab/SpatialSort.

RUNX1 colludes with NOTCH1 to reprogram chromatin in T cell acute lymphoblastic leukemia.

Runt-related transcription factor 1 (RUNX1) is oncogenic in diverse types of leukemia and epithelial cancers where its expression is associated with poor prognosis. Current models suggest that RUNX1 cooperates with other oncogenic factors (e.g., NOTCH1, TAL1) to drive the expression of proto-oncogenes in T cell acute lymphoblastic leukemia (T-ALL) but the molecular mechanisms controlled by RUNX1 and its cooperation with other factors remain unclear. Integrative chromatin and transcriptional analysis following inhibition of RUNX1 and NOTCH1 revealed a surprisingly widespread role of RUNX1 in the establishment of global H3K27ac levels and that RUNX1 is required by NOTCH1 for cooperative transcription activation of key NOTCH1 target genes including MYC, DTX1, HES4, IL7R, and NOTCH3. Super-enhancers were preferentially sensitive to RUNX1 knockdown and RUNX1-dependent super-enhancers were disrupted following the treatment of a pan-BET inhibitor, I-BET151.

KDM6B protects T-ALL cells from NOTCH1-induced oncogenic stress.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematopoietic neoplasm resulting from the malignant transformation of T-cell progenitors. While activating NOTCH1 mutations are the dominant genetic drivers of T-ALL, epigenetic dysfunction plays a central role in the pathology of T-ALL and can provide alternative mechanisms to oncogenesis in lieu of or in combination with genetic mutations. The histone demethylase enzyme KDM6A (UTX) is also recurrently mutated in T-ALL patients and functions as a tumor suppressor. However, its gene paralog, KDM6B (JMJD3), is never mutated and can be significantly overexpressed, suggesting it may be necessary for sustaining the disease. Here, we used mouse and human T-ALL models to show that KDM6B is required for T-ALL development and maintenance. Using NOTCH1 gain-of-function retroviral models, mouse cells genetically deficient for Kdm6b were unable to propagate T-ALL. Inactivating KDM6B in human T-ALL patient cells by CRISPR/Cas9 showed KDM6B-targeted cells were significantly outcompeted over time. The dependence of T-ALL cells on KDM6B was proportional to the oncogenic strength of NOTCH1 mutation, with KDM6B required to prevent stress-induced apoptosis from strong NOTCH1 signaling. These studies identify a crucial role for KDM6B in sustaining NOTCH1-driven T-ALL and implicate KDM6B as a novel therapeutic target in these patients.

Noncanonical ß-catenin interactions promote leukemia-initiating activity in early T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia (T-ALL) is a T-cell malignancy characterized by cell subsets and enriched with leukemia-initiating cells (LICs). ß-Catenin modulates LIC activity in T-ALL. However, its role in maintaining established leukemia stem cells remains largely unknown. To identify functionally relevant protein interactions of ß-catenin in T-ALL, we performed coimmunoprecipitation followed by liquid chromatography-mass spectrometry. Here, we report that a noncanonical functional interaction of ß-catenin with the Forkhead box O3 (FOXO3) transcription factor positively regulates LIC-related genes, including the cyclin-dependent kinase 4, which is a crucial modulator of cell cycle and tumor maintenance. We also confirm the relevance of these findings using stably integrated fluorescent reporters of ß-catenin and FOXO3 activity in patient-derived xenografts, which identify minor subpopulations with enriched LIC activity. In addition, gene expression data at the single-cell level of leukemic cells of primary patients at the time of diagnosis and minimal residual disease (MRD) up to 30 days after the standard treatments reveal that the expression of ß-catenin- and FOXO3-dependent genes is present in the CD82+CD117+ cell fraction, which is substantially enriched with LICs in MRD as well as in early T-cell precursor ALL. These findings highlight key functional roles for ß-catenin and FOXO3 and suggest novel therapeutic strategies to eradicate aggressive cell subsets in T-ALL.

Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk.

Follicular lymphoma (FL) is an indolent cancer of mature B-cells but with ongoing risk of transformation to more aggressive histology over time. Recurrent mutations associated with transformation have been identified; however, prognostic features that can be discerned at diagnosis could be clinically useful. We present here comprehensive profiling of both tumor and immune compartments in 155 diagnostic FL biopsies at single-cell resolution by mass cytometry. This revealed a diversity of phenotypes but included two recurrent patterns, one which closely resembles germinal center B-cells (GCB) and another which appears more related to memory B-cells (MB). GCB-type tumors are enriched for EZH2, TNFRSF14, and MEF2B mutations, while MB-type tumors contain increased follicular helper T-cells. MB-type and intratumoral phenotypic diversity are independently associated with increased risk of transformation, supporting biological relevance of these features. Notably, a reduced 26-marker panel retains sufficient information to allow phenotypic profiling of future cohorts by conventional flow cytometry.

Comprehensive immune profiling of patients with advanced urothelial or renal cell carcinoma receiving immune checkpoint blockade.

Immune checkpoint inhibitors (ICI) are used in the treatment of urothelial and renal cell cancers. While some patients may have exceptional responses, better predictive biomarkers are needed. We profiled the circulating immune compartment of patients receiving ICI to identify possible immune markers associated with immunotherapy response or resistance. Peripheral blood samples were collected prior to, and 3 weeks after initiation of ICI. Using mass cytometry, 26 distinct immune populations were identified. Responders to immune checkpoint inhibitors had higher frequencies of naïve CD4+ T-cells, and lower frequencies of CD161+ Th17 cells and CCR4+ Th2 cells. Non-responders had a higher frequency of circulating PD1+ T-cells at baseline; there was a subsequent decrease in frequency with exposure to ICI with a concomitant increase in Ki67 expression. Flow cytometry for cytokines and chemokine receptors showed that CD4+ T cells of non-responder patients expressed less CXCR4 and CCR7. In addition, their PD1- CD4+ T cells had higher TNFα and higher CCR4 expression, while their PD1+ CD4+ T cells had higher interferon γ and lower CCR4 expression. The role of γ/δ T-cells was also explored. In responders, these cells had higher levels of interferon γ, TNFα and CCR5. One patient with a complete response had markedly higher frequency of γ/δ T-cells at baseline, and an expansion of these cells after treatment. This case was analyzed using single-cell gene expression profiling. The bulk of the γ/δ T cells consisted of a single clone of Vγ9/Vδ2 cells both before and after expansion, although the expansion was polyclonal. Gene expression analysis showed that exposure to an ICI led to a more activated phenotype of the γ/δ T cells. In this study, the circulating immune compartment was shown to have potential for biomarker discovery. Its dynamic changes during treatment may be used to assess response before radiographic changes are apparent, and these changes may help us delineate mechanisms that underpin both response and resistance to ICI. It also hypothesizes a potential role for γ/δ T cells as effector cells in some cases.

Tcf1 is essential for initiation of oncogenic Notch1-driven chromatin topology in T-ALL.

NOTCH1 is a well-established lineage specifier for T cells and among the most frequently mutated genes throughout all subclasses of T cell acute lymphoblastic leukemia (T-ALL). How oncogenic NOTCH1 signaling launches a leukemia-prone chromatin landscape during T-ALL initiation is unknown. Here we demonstrate an essential role for the high-mobility-group transcription factor Tcf1 in orchestrating chromatin accessibility and topology, allowing aberrant Notch1 signaling to convey its oncogenic function. Although essential, Tcf1 is not sufficient to initiate leukemia. The formation of a leukemia-prone epigenetic landscape at the distal Notch1-regulated Myc enhancer, which is fundamental to this disease, is Tcf1-dependent and occurs within the earliest progenitor stage even before cells adopt a T lymphocyte or leukemic fate. Moreover, we discovered a unique evolutionarily conserved Tcf1-regulated enhancer element in the distal Myc-enhancer, which is important for the transition of preleukemic cells to full-blown disease.

CRIS: complete reconstruction of immunoglobulin V-D-J sequences from RNA-seq data.

MOTIVATION: B cells display remarkable diversity in producing B-cell receptors through recombination of immunoglobulin (Ig) V-D-J genes. Somatic hypermutation (SHM) of immunoglobulin heavy chain variable (IGHV) genes are used as a prognostic marker in B-cell malignancies. Clinically, IGHV mutation status is determined by targeted Sanger sequencing which is a resource-intensive and low-throughput procedure. Here, we describe a bioinformatic pipeline, CRIS (Complete Reconstruction of Immunoglobulin IGHV-D-J Sequences) that uses RNA sequencing (RNA-seq) datasets to reconstruct IGHV-D-J sequences and determine IGHV SHM status. RESULTS: CRIS extracts RNA-seq reads aligned to Ig gene loci, performs assembly of Ig transcripts and aligns the resulting contigs to reference Ig sequences to enumerate and classify SHMs in the IGHV gene sequence. CRIS improves on existing tools that infer the B-cell receptor repertoire from RNA-seq data using a portion IGHV gene segment by de novo assembly. We show that the SHM status identified by CRIS using the entire IGHV gene segment is highly concordant with clinical classification in three independent chronic lymphocytic leukemia patient cohorts. AVAILABILITY AND IMPLEMENTATION: The CRIS pipeline is available under the MIT License from https://github.com/Rashedul/CRIS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Advances online.

Single-cell profiling reveals the importance of CXCL13/CXCR5 axis biology in lymphocyte-rich classic Hodgkin lymphoma.

Lymphocyte-rich classic Hodgkin lymphoma (LR-CHL) is a rare subtype of Hodgkin lymphoma. Recent technical advances have allowed for the characterization of specific cross-talk mechanisms between malignant Hodgkin Reed-Sternberg (HRS) cells and different normal immune cells in the tumor microenvironment (TME) of CHL. However, the TME of LR-CHL has not yet been characterized at single-cell resolution. Here, using single-cell RNA sequencing (scRNA-seq), we examined the immune cell profile of 8 cell suspension samples of LR-CHL in comparison to 20 samples of the mixed cellularity (MC, 9 cases) and nodular sclerosis (NS, 11 cases) subtypes of CHL, as well as 5 reactive lymph node controls. We also performed multicolor immunofluorescence (MC-IF) on tissue microarrays from the same patients and an independent validation cohort of 31 pretreatment LR-CHL samples. ScRNA-seq analysis identified a unique CD4+ helper T cell subset in LR-CHL characterized by high expression of Chemokine C-X-C motif ligand 13 (CXCL13) and PD-1. PD-1+CXCL13+ T cells were significantly enriched in LR-CHL compared to other CHL subtypes, and spatial analyses revealed that in 46% of the LR-CHL cases these cells formed rosettes surrounding HRS cells. MC-IF analysis revealed CXCR5+ normal B cells in close proximity to CXCL13+ T cells at significantly higher levels in LR-CHL. Moreover, the abundance of PD-1+CXCL13+ T cells in the TME was significantly associated with shorter progression-free survival in LR-CHL (P = 0.032). Taken together, our findings strongly suggest the pathogenic importance of the CXCL13/CXCR5 axis and PD-1+CXCL13+ T cells as a treatment target in LR-CHL.