Spatially Resolved Single-Cell Omics: Methods, Challenges, and Future Perspectives.

Overlaying omics data onto spatial biological dimensions has been a promising technology to provide high-resolution insights into the interactome and cellular heterogeneity relative to the organization of the molecular microenvironment of tissue samples in normal and disease states. Spatial omics can be categorized into three major modalities: (a) next-generation sequencing-based assays, (b) imaging-based spatially resolved transcriptomics RNA approaches including in situ hybridization/in situ sequencing, and (c) imaging-based proteomics. These modalities allow assessment of transcripts and proteins at a cellular level, generating large and computationally challenging datasets. The lack of standardized computational pipelines to analyze and integrate these nonuniform structured data has made it necessary to apply artificial intelligence and machine learning strategies to best visualize and translate their complexity. In this review, we summarize the currently available techniques and computational strategies, highlight their advantages and limitations, and discuss their future prospects in the scientific field.

Cis- and trans-eQTL TWASs of breast and ovarian cancer identify more than 100 susceptibility genes in the BCAC and OCAC consortia.

Transcriptome-wide association studies (TWASs) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have focused on the regulatory effects of risk-associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWASs of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole-genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents an in-depth look into the role of trans eQTLs in the complex molecular mechanisms underlying these diseases.

Lesion-remote astrocytes govern microglia-mediated white matter repair.

Spared regions of the damaged central nervous system undergo dynamic remodeling and exhibit a remarkable potential for therapeutic exploitation. Here, lesion-remote astrocytes (LRAs), which interact with viable neurons, glia and neural circuitry, undergo reactive transformations whose molecular and functional properties are poorly understood. Using multiple transcriptional profiling methods, we interrogated LRAs from spared regions of mouse spinal cord following traumatic spinal cord injury (SCI). We show that LRAs acquire a spectrum of molecularly distinct, neuroanatomically restricted reactivity states that evolve after SCI. We identify transcriptionally unique reactive LRAs in degenerating white matter that direct the specification and function of local microglia that clear lipid-rich myelin debris to promote tissue repair. Fueling this LRA functional adaptation is Ccn1 , which encodes for a secreted matricellular protein. Loss of astrocyte CCN1 leads to excessive, aberrant activation of local microglia with (i) abnormal molecular specification, (ii) dysfunctional myelin debris processing, and (iii) impaired lipid metabolism, culminating in blunted debris clearance and attenuated neurological recovery from SCI. Ccn1 -expressing white matter astrocytes are specifically induced by local myelin damage and generated in diverse demyelinating disorders in mouse and human, pointing to their fundamental, evolutionarily conserved role in white matter repair. Our findings show that LRAs assume regionally divergent reactivity states with functional adaptations that are induced by local context-specific triggers and influence disorder outcome. Astrocytes tile the central nervous system (CNS) where they serve vital roles that uphold healthy nervous system function, including regulation of synapse development, buffering of neurotransmitters and ions, and provision of metabolic substrates 1 . In response to diverse CNS insults, astrocytes exhibit disorder-context specific transformations that are collectively referred to as reactivity 2-5 . The characteristics of regionally and molecularly distinct reactivity states are incompletely understood. The mechanisms through which distinct reactivity states arise, how they evolve or resolve over time, and their consequences for local cell function and CNS disorder progression remain enigmatic. Immediately adjacent to CNS lesions, border-forming astrocytes (BFAs) undergo transcriptional reprogramming and proliferation to form a neuroprotective barrier that restricts inflammation and supports axon regeneration 6-9 . Beyond the lesion, spared but dynamic regions of the injured CNS exhibit varying degrees of synaptic circuit remodeling and progressive cellular responses to secondary damage that have profound consequences for neural repair and recovery 10,11 . Throughout these cytoarchitecturally intact, but injury-reactive regions, lesion-remote astrocytes (LRAs) intermingle with neurons and glia, undergo little to no proliferation, and exhibit varying degrees of cellular hypertrophy 7,12,13 . The molecular and functional properties of LRAs remain grossly undefined. Therapeutically harnessing spared regions of the injured CNS will require a clearer understanding of the accompanying cellular and molecular landscape. Here, we leveraged integrative transcriptional profiling methodologies to identify multiple spatiotemporally resolved, molecularly distinct states of LRA reactivity within the injured spinal cord. Computational modeling of LRA-mediated heterotypic cell interactions, astrocyte-specific conditional gene deletion, and multiple mouse models of acute and chronic CNS white matter degeneration were used to interrogate a newly identified white matter degeneration-reactive astrocyte subtype. We define how this reactivity state is induced and its role in governing the molecular and functional specification of local microglia that clear myelin debris from the degenerating white matter to promote repair.

FixNCut: single-cell genomics through reversible tissue fixation and dissociation.

The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.

Multi-lineage heart-chip models drug cardiotoxicity and enhances maturation of human stem cell-derived cardiovascular cells.

Cardiovascular toxicity causes adverse drug reactions and may lead to drug removal from the pharmaceutical market. Cancer therapies can induce life-threatening cardiovascular side effects such as arrhythmias, muscle cell death, or vascular dysfunction. New technologies have enabled cardiotoxic compounds to be identified earlier in drug development. Human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs) and vascular endothelial cells (ECs) can screen for drug-induced alterations in cardiovascular cell function and survival. However, most existing hiPSC models for cardiovascular drug toxicity utilize two-dimensional, immature cells grown in static culture. Improved in vitro models to mechanistically interrogate cardiotoxicity would utilize more adult-like, mature hiPSC-derived cells in an integrated system whereby toxic drugs and protective agents can flow between hiPSC-ECs that represent systemic vasculature and hiPSC-CMs that represent heart muscle (myocardium). Such models would be useful for testing the multi-lineage cardiotoxicities of chemotherapeutic drugs such as VEGFR2/PDGFR-inhibiting tyrosine kinase inhibitors (VPTKIs). Here, we develop a multi-lineage, fully-integrated, cardiovascular organ-chip that can enhance hiPSC-EC and hiPSC-CM functional and genetic maturity, model endothelial barrier permeability, and demonstrate long-term functional stability. This microfluidic organ-chip harbors hiPSC-CMs and hiPSC-ECs on separate channels that can be subjected to active fluid flow and rhythmic biomechanical stretch. We demonstrate the utility of this cardiovascular organ-chip as a predictive platform for evaluating multi-lineage VPTKI toxicity. This study may lead to the development of new modalities for the evaluation and prevention of cancer therapy-induced cardiotoxicity.

Cis- and trans-eQTL TWAS of breast and ovarian cancer identify more than 100 risk associated genes in the BCAC and OCAC consortia.

Transcriptome-wide association studies (TWAS) have investigated the role of genetically regulated transcriptional activity in the etiologies of breast and ovarian cancer. However, methods performed to date have only considered regulatory effects of risk associated SNPs thought to act in cis on a nearby target gene. With growing evidence for distal (trans) regulatory effects of variants on gene expression, we performed TWAS of breast and ovarian cancer using a Bayesian genome-wide TWAS method (BGW-TWAS) that considers effects of both cis- and trans-expression quantitative trait loci (eQTLs). We applied BGW-TWAS to whole genome and RNA sequencing data in breast and ovarian tissues from the Genotype-Tissue Expression project to train expression imputation models. We applied these models to large-scale GWAS summary statistic data from the Breast Cancer and Ovarian Cancer Association Consortia to identify genes associated with risk of overall breast cancer, non-mucinous epithelial ovarian cancer, and 10 cancer subtypes. We identified 101 genes significantly associated with risk with breast cancer phenotypes and 8 with ovarian phenotypes. These loci include established risk genes and several novel candidate risk loci, such as ACAP3, whose associations are predominantly driven by trans-eQTLs. We replicated several associations using summary statistics from an independent GWAS of these cancer phenotypes. We further used genotype and expression data in normal and tumor breast tissue from the Cancer Genome Atlas to examine the performance of our trained expression imputation models. This work represents a first look into the role of trans-eQTLs in the complex molecular mechanisms underlying these diseases.

A machine learning one-class logistic regression model to predict stemness for single cell transcriptomics and spatial omics.

Cell annotation is a crucial methodological component to interpreting single cell and spatial omics data. These approaches were developed for single cell analysis but are often biased, manually curated and yet unproven in spatial omics. Here we apply a stemness model for assessing oncogenic states to single cell and spatial omic cancer datasets. This one-class logistic regression machine learning algorithm is used to extract transcriptomic features from non-transformed stem cells to identify dedifferentiated cell states in tumors. We found this method identifies single cell states in metastatic tumor cell populations without the requirement of cell annotation. This machine learning model identified stem-like cell populations not identified in single cell or spatial transcriptomic analysis using existing methods. For the first time, we demonstrate the application of a ML tool across five emerging spatial transcriptomic and proteomic technologies to identify oncogenic stem-like cell types in the tumor microenvironment.

Challenges and Opportunities in Building a Global Representative Single-Cell and Spatial Atlas in Cancer.

SUMMARY: Cancer health disparities are complex and a mixture of factors that need to be accounted for in both our planning, implementation, and execution across all researchers, especially in single-cell and spatial technologies, which have a higher burden for adoption in low- and middle-income countries. This commentary tackles the hurdles these technologies face in creating a diverse, representative atlas of cancer and is a call to arms for a strategic plan toward inclusivity across all global populations.

Incidence and prognostic impact of HER2-positivity loss after dual HER2-directed neoadjuvant therapy for HER2+ breast cancer.

BACKGROUND: Loss of HER2 "positivity" can occur in patients with residual disease after neoadjuvant treatment, but the incidence of HER2-positivity loss after neoadjuvant dual HER2-targeted treatment plus chemotherapy, the current standard-of-care for most early stage HER2-positive breast cancers, is not well described. Previous studies that report the HER2 discordance rate after neoadjuvant treatment also do not include the novel HER2-low category. In this retrospective study, we determine the incidence and prognostic impact of HER2-positivity loss, including the evolution to HER2-low disease, after neoadjuvant dual HER2-targeted therapy with chemotherapy. METHODS: Clinicopathologic data for patients with stage I-III HER2+ breast cancer diagnosed between 2015 and 2019 were reviewed in this single institution retrospective study. Patients who received dual HER2-targeted treatment with chemotherapy were included, and HER2 status before and after neoadjuvant therapy was interrogated. RESULTS: A total of 163 female patients were included in the analysis with a median age of 50 years. A pathologic complete response (pCR as defined by ypT0/is) was achieved in 102 (62.5%) of 163 evaluable patients. Among the 61 patients with residual disease after neoadjuvant therapy, 36 (59.0%) had HER2-positive and 25 (41.0%) had HER2-negative residual disease. Of the 25 patients with HER2-negative residual disease, 22 (88%) of patients were classified as HER2-low. After a median follow-up of 3.3 years, patients who retained HER2-positivity after neoadjuvant treatment had a 3-year IDFS rate of 91% (95% CI, 91%-100%), while patients who lost HER2-positivity had a 3-year IDFS rate of 82% (95% CI, 67%-100%). CONCLUSION: Almost half of patients with residual disease following neoadjuvant dual HER2-targeted therapy plus chemotherapy lost HER2-positivity. The loss of HER2-positivity may not confer negative prognostic impact, although the results were limited by short follow-up time. Further research on the HER2 status after neoadjuvant treatment may help guide treatment decisions in the adjuvant setting.

Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer's disease.

Human middle temporal gyrus (MTG) is a vulnerable brain region in early Alzheimer's disease (AD), but little is known about the molecular mechanisms underlying this regional vulnerability. Here we utilize the 10 × Visium platform to define the spatial transcriptomic profile in both AD and control (CT) MTG. We identify unique marker genes for cortical layers and the white matter, and layer-specific differentially expressed genes (DEGs) in human AD compared to CT. Deconvolution of the Visium spots showcases the significant difference in particular cell types among cortical layers and the white matter. Gene co-expression analyses reveal eight gene modules, four of which have significantly altered co-expression patterns in the presence of AD pathology. The co-expression patterns of hub genes and enriched pathways in the presence of AD pathology indicate an important role of cell-cell-communications among microglia, oligodendrocytes, astrocytes, and neurons, which may contribute to the cellular and regional vulnerability in early AD. Using single-molecule fluorescent in situ hybridization, we validated the cell-type-specific expression of three novel DEGs (e.g., KIF5A, PAQR6, and SLC1A3) and eleven previously reported DEGs associated with AD pathology (i.e., amyloid beta plaques and intraneuronal neurofibrillary tangles or neuropil threads) at the single cell level. Our results may contribute to the understanding of the complex architecture and neuronal and glial response to AD pathology of this vulnerable brain region.

Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.

BACKGROUND: Known risk alleles for epithelial ovarian cancer (EOC) account for approximately 40% of the heritability for EOC. Copy number variants (CNVs) have not been investigated as EOC risk alleles in a large population cohort. METHODS: Single nucleotide polymorphism array data from 13 071 EOC cases and 17 306 controls of White European ancestry were used to identify CNVs associated with EOC risk using a rare admixture maximum likelihood test for gene burden and a by-probe ratio test. We performed enrichment analysis of CNVs at known EOC risk loci and functional biofeatures in ovarian cancer-related cell types. RESULTS: We identified statistically significant risk associations with CNVs at known EOC risk genes; BRCA1 (PEOC = 1.60E-21; OREOC = 8.24), RAD51C (Phigh-grade serous ovarian cancer [HGSOC] = 5.5E-4; odds ratio [OR]HGSOC = 5.74 del), and BRCA2 (PHGSOC = 7.0E-4; ORHGSOC = 3.31 deletion). Four suggestive associations (P < .001) were identified for rare CNVs. Risk-associated CNVs were enriched (P < .05) at known EOC risk loci identified by genome-wide association study. Noncoding CNVs were enriched in active promoters and insulators in EOC-related cell types. CONCLUSIONS: CNVs in BRCA1 have been previously reported in smaller studies, but their observed frequency in this large population-based cohort, along with the CNVs observed at BRCA2 and RAD51C gene loci in EOC cases, suggests that these CNVs are potentially pathogenic and may contribute to the spectrum of disease-causing mutations in these genes. CNVs are likely to occur in a wider set of susceptibility regions, with potential implications for clinical genetic testing and disease prevention.

Comparative Upper Respiratory Tract Transcriptomic Profiling Reveals a Potential Role of Early Activation of Interferon Pathway in Severe COVID-19.

Infection with SARS-CoV-2 results in Coronavirus disease 2019 (COVID-19) is known to cause mild to acute respiratory infection and sometimes progress towards respiratory failure and death. The mechanisms driving the progression of the disease and accumulation of high viral load in the lungs without initial symptoms remain elusive. In this study, we evaluated the upper respiratory tract host transcriptional response in COVID-19 patients with mild to severe symptoms and compared it with the control COVID-19 negative group using RNA-sequencing (RNA-Seq). Our results reveal an upregulated early type I interferon response in severe COVID-19 patients as compared to mild or negative COVID-19 patients. Moreover, severely symptomatic patients have pronounced induction of interferon stimulated genes (ISGs), particularly the oligoadenylate synthetase (OAS) family of genes. Our results are in concurrence with other studies depicting the early induction of IFN-I response in severe COVID-19 patients, providing novel insights about the ISGs involved.

DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers.

BACKGROUND: Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). METHODS: We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations. RESULTS: Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers. CONCLUSION: These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Dual Stromal Targeting Sensitizes Pancreatic Adenocarcinoma for Anti-Programmed Cell Death Protein 1 Therapy.

BACKGROUND & AIMS: The stroma in pancreatic ductal adenocarcinoma (PDAC) contributes to its immunosuppressive nature and therapeutic resistance. Herein we sought to modify signaling and enhance immunotherapy efficacy by targeting multiple stromal components through both intracellular and extracellular mechanisms. METHODS: A murine liver metastasis syngeneic model of PDAC was treated with focal adhesion kinase inhibitor (FAKi), anti-programmed cell death protein 1 (PD-1) antibody, and stromal hyaluronan (HA) degradation by PEGylated recombinant human hyaluronidase (PEGPH20) to assess immune and stromal modulating effects of these agents and their combinations. RESULTS: The results showed that HA degradation by PEGPH20 and reduction in phosphorylated FAK expression by FAKi leads to improved survival in PDAC-bearing mice treated with anti-PD-1 antibody. HA degradation in combination with FAKi and anti-PD-1 antibody increases T-cell infiltration and alters T-cell phenotype toward effector memory T cells. FAKi alters the expression of T-cell modulating cytokines and leads to changes in T-cell metabolism and increases in effector T-cell signatures. HA degradation in combination with anti-PD-1 antibody and FAKi treatments reduces granulocytes, including granulocytic- myeloid-derived suppressor cells and decreases C-X-C chemokine receptor type 4 (CXCR4)-expressing myeloid cells, particularly the CXCR4-expressing granulocytes. Anti-CXCR4 antibody combined with FAKi and anti-PD-1 antibody significantly decreases metastatic rates in the PDAC liver metastasis model. CONCLUSIONS: This represents the first preclinical study to identify synergistic effects of targeting both intracellular and extracellular components within the PDAC stroma and supports testing anti-CXCR4 antibody in combination with FAKi as a PDAC treatment strategy.

US Severe Acute Respiratory Syndrome Coronavirus 2 Epsilon Variant: Highly Transmissible but With an Adjusted Muted Host T-Cell Response.

BACKGROUND: The multiple mutations comprising the epsilon variant demonstrate the independent convergent evolution of severe acute respiratory syndrome coronavirus (SARS-CoV-2), with its spike protein mutation L452R present in the delta (L452R), kappa (L452R), and lambda (L452Q) variants. METHODS: Coronavirus disease 2019 (COVID-19) variants were detected in 1017 patients using whole-genome sequencing and were assessed for outcome and severity. The mechanistic effects of the epsilon versus non-epsilon variants were investigated using a multiomic approach including cellular response assays and paired cell and host transcriptomic and proteomic profiling. RESULTS: We found that patients carrying the epsilon variant had increased mortality risk but not increased hospitalizations (P < .02). Cells infected with live epsilon compared with non-epsilon virus displayed increased sensitivity to neutralization antibodies in all patients but a slightly protective response in vaccinated individuals (P < .001). That the epsilon SARS-CoV-2 variant is more infectious but less virulent is supported mechanistically in the down-regulation of viral processing pathways seen by multiomic analyses. Importantly, this paired transcriptomics and proteomic profiling of host cellular response to live virus revealed an altered leukocyte response and metabolic messenger RNA processing with the epsilon variant. To ascertain host response to SARS-CoV-2 infection, primary COVID-19-positive nasopharyngeal samples were transcriptomically profiled and revealed a differential innate immune response (P < .001) and an adjusted T-cell response in patients carrying the epsilon variant (P < .002). In fact, patients infected with SARS-CoV-2 and those vaccinated with the BNT162b2 vaccine have comparable CD4+/CD8+ T-cell immune responses to the epsilon variant (P < .05). CONCLUSIONS: While the epsilon variant is more infectious, by altering viral processing, we showed that patients with COVID-19 have adapted their innate immune response to this fitter variant. A protective T-cell response molecular signature is generated by this more transmissible variant in both vaccinated and unvaccinated patients.

Human iPSC-derived fallopian tube organoids with BRCA1 mutation recapitulate early-stage carcinogenesis.

Germline pathogenic mutations in BReast CAncer (BRCA1) genes are thought to drive normal fallopian tube epithelial (FTE) cell transformation to high-grade serous ovarian cancer. No human models capture the sequence of events for disease initiation and progression. Here, we generate induced pluripotent stem cells (iPSCs) from healthy individuals and young ovarian cancer patients with germline pathogenic BRCA1 mutations (BRCA1mut). Following differentiation into FTE organoids, BRCA1mut lines exhibit cellular abnormalities consistent with neoplastic transformation compared to controls. BRCA1mut organoids show an increased production of cancer-specific proteins and survival following transplantation into mice. Organoids from women with the most aggressive ovarian cancer show the greatest pathology, indicating the potential value to predict clinical severity prior to disease onset. These human FTE organoids from BRCA1mut carriers provide a faithful physiological in vitro model of FTE lesion generation and early carcinogenesis. This platform can be used for personalized mechanistic and drug screening studies.

Risks and Function of Breast Cancer Susceptibility Alleles.

Family history remains one of the strongest risk factors for breast cancer. It is well established that women with a first-degree relative affected by breast cancer are twice as likely to develop the disease themselves. Twins studies indicate that this is most likely due to shared genetics rather than shared epidemiological/lifestyle risk factors. Linkage and targeted sequencing studies have shown that rare high- and moderate-penetrance germline variants in genes involved in the DNA damage response (DDR) including BRCA1, BRCA2, PALB2, ATM, and TP53 are responsible for a proportion of breast cancer cases. However, breast cancer is a heterogeneous disease, and there is now strong evidence that different risk alleles can predispose to different subtypes of breast cancer. Here, we review the associations between the different genes and subtype-specificity of breast cancer based on the most comprehensive genetic studies published. Genome-wide association studies (GWAS) have also been used to identify an additional hereditary component of breast cancer, and have identified hundreds of common, low-penetrance susceptibility alleles. The combination of these low penetrance risk variants, summed as a polygenic risk score (PRS), can identify individuals across the spectrum of disease risk. However, there remains a substantial bottleneck between the discovery of GWAS-risk variants and their contribution to tumorigenesis mainly because the majority of these variants map to the non-protein coding genome. A range of functional genomic approaches are needed to identify the causal risk variants and target susceptibility genes and establish their underlying role in disease biology. We discuss how the application of these multidisciplinary approaches to understand genetic risk for breast cancer can be used to identify individuals in the population that may benefit from clinical interventions including screening for early detection and prevention, and treatment strategies to reduce breast cancer-related mortalities.

Evidence of disrupted rhombic lip development in the pathogenesis of Dandy-Walker malformation.

Dandy-Walker malformation (DWM) and Cerebellar vermis hypoplasia (CVH) are commonly recognized human cerebellar malformations diagnosed following ultrasound and antenatal or postnatal MRI. Specific radiological criteria are used to distinguish them, yet little is known about their differential developmental disease mechanisms. We acquired prenatal cases diagnosed as DWM and CVH and studied cerebellar morphobiometry followed by histological and immunohistochemical analyses. This was supplemented by laser capture microdissection and RNA-sequencing of the cerebellar rhombic lip, a transient progenitor zone, to assess the altered transcriptome of DWM vs control samples. Our radiological findings confirm that the cases studied fall within the accepted biometric range of DWM. Our histopathological analysis points to reduced foliation and inferior vermian hypoplasia as common features in all examined DWM cases. We also find that the rhombic lip, a dorsal stem cell zone that drives the growth and maintenance of the posterior vermis is specifically disrupted in DWM, with reduced proliferation and self-renewal of the progenitor pool, and altered vasculature, all confirmed by transcriptomics analysis. We propose a unified model for the developmental pathogenesis of DWM. We hypothesize that rhombic lip development is disrupted through either aberrant vascularization and/or direct insult which causes reduced proliferation and failed expansion of the rhombic lip progenitor pool leading to disproportionate hypoplasia and dysplasia of the inferior vermis. Timing of insult to the developing rhombic lip (before or after 14 PCW) dictates the extent of hypoplasia and distinguishes DWM from CVH.

An N-Cadherin 2 expressing epithelial cell subpopulation predicts response to surgery, chemotherapy and immunotherapy in bladder cancer.

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) have revolutionized bladder cancer management. However, stratification of patients that would benefit most from these modalities remains a major clinical challenge. Here, we combine single nuclei RNA sequencing with spatial transcriptomics and single-cell resolution spatial proteomic analysis of human bladder cancer to identify an epithelial subpopulation with therapeutic response prediction ability. These cells express Cadherin 12 (CDH12, N-Cadherin 2), catenins, and other epithelial markers. CDH12-enriched tumors define patients with poor outcome following surgery with or without NAC. In contrast, CDH12-enriched tumors exhibit superior response to ICT. In all settings, patient stratification by tumor CDH12 enrichment offers better prediction of outcome than currently established bladder cancer subtypes. Molecularly, the CDH12 population resembles an undifferentiated state with inherently aggressive biology including chemoresistance, likely mediated through progenitor-like gene expression and fibroblast activation. CDH12-enriched cells express PD-L1 and PD-L2 and co-localize with exhausted T-cells, possibly mediated through CD49a (ITGA1), providing one explanation for ICT efficacy in these tumors. Altogether, this study describes a cancer cell population with an intriguing diametric response to major bladder cancer therapeutics. Importantly, it also provides a compelling framework for designing biomarker-guided clinical trials.